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Job DescriptionAbout SmartAsset: SmartAsset is an online destination for consumer-focused financial information and advice, whose mission is helping people make smart financial decisions, reaching over an estimated 59 million people each month (as of January 2025) through our educational content and personalized calculators and tools. To extend our mission, we also operate SmartAsset Advisor Marketing Platform (AMP), which helps connect consumers with fiduciary financial advisors.SmartAsset has earned recognition on the Inc. 5000 (#2574 in 2023) and Deloitte Technology Fast 500™ (#250 in 2022) lists. Currently, SmartAsset ranks on Y Combinator's list of Top 100 Companies. A successful $110 million Series D funding round in 2021 valued the company at over $1 billion. *Other than application and licensing fees, SmartAsset did not provide compensation for the aforementioned awards. About the team: The Machine Learning Engineering team designs, builds, and integrates the core platform that unlocks cutting-edge capabilities for financial advisors, including features driven by generative AI. Our engineers are relentlessly evolving this platform, empowering groundbreaking applications and features that truly help financial professionals better connect with their clients and grow their businesses. About the Job: We are seeking a highly motivated and experienced Machine Learning Engineer to join our growing team. In this role, you will be instrumental in crafting and scaling foundational backend systems across predictive systems and generative AI. You will work across the entire software development lifecycle, from architectural design to deployment and ongoing operations, contributing significantly to our core infrastructure and data strategies, and working hand-in-hand with cross-functional partners like LLM Engineers, Product Owners, and Data Scientists to bring our vision to life. Responsibilities: • Design, develop, and maintain high-performance, scalable, and secure backend services, primarily using Python and frameworks like FastAPI, • Translate ambiguous business and technical requirements into concrete software designs and actionable tasks for cross-functional teams, • Work with OLTP databases, including schema design, migration strategies, and performance optimization, • Integrate SmartAsset services with internal and external APIs, including third-party platforms and existing AWS infrastructure, • Ensure secure ingress and egress of data within our private network environments, • Contribute to the design and implementation of our CI/CD pipelines to ensure continual improvements to our cycle time, • Manage and optimize AWS services, including IAM roles and policies, • Gain a deep understanding of how our Python applications integrate with our Kubernetes (EKS) and future ECS-based infrastructure, • Operate and maintain production applications at scale, ensuring high availability, performance, and reliability, • Design and implement data collection pipelines specifically for Large Language Models (LLMs), • Contributed to shared data architecture and data governance practices to ensure the persistence of structured data suitable for analytics and model training, • Explore, integrate, and tune various LLM-related technologies, such as Retrieval Augmented Generation (RAG) systems, and addressing potential scaling challenges, • Investigate and implement agentic technologies, such as tool calling frameworks (e.g., AutoGen), to enhance LLM capabilities, • Proven experience as a ML Engineer with a strong focus on Python development, • Experience with cloud platforms, specifically AWS, including IAM, EKS/ECS, and other core services, • Strong expertise with OLTP/relational databases such as Aurora, Postgres, MySQL etc, • Experience with DevOps toolsets such as Terraform, Open-Telemetry, etc. will be a big plus, • Strong experience in developing and maintaining large-scale, production-grade applications, • Experience in writing clean, maintainable, and testable code following best practices and industry standards, • Experience building integrations with internal and external service providers, • At least 5 years of relevant working experience., • Excellent communication skills, both written and verbal, • Experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, etc., • Experience with LLMs, RAG, embedding vector databases, or agentic technologies., • Familiarity with productionizing apps built with prototyping frameworks such as Streamlit or Gradio, • Knowledge of data governance and structured data principles, • Prolonged periods of sitting at a desk and working on a computer, • Must be able to communicate via phone calls and/or video conferences (mainly for concierge and sales roles) Available Benefits and Perks:, • All roles at SmartAsset are currently and will remain remote - flexibility to work from anywhere in the Contiguous US., • Medical, Dental, Vision - multiple packages available based on your individualized needs, • Life/AD&D Insurance - basic coverage at 100% company paid, additional supplemental available, • Supplemental Short-term and Long-term Disability, • FSA: Medical and Dependant Care, • 401K, • Equity packages for each role, • Time Off: Vacation, Sick and Parental Leave, • EAP (Employee Assistance Program), • Financial Literacy Mentoring Program, • Pet Insurance California, Colorado, Connecticut, Maryland, Nevada, Rhode Island, Washington, and New York City residents $137,000 - $180,000 + RSUs + benefits. Salary at SmartAsset is determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location within the contiguous United States.

Job DescriptionA little about us… Knit is the AI-native consumer research platform helping brands automate and accelerate primary research. With our Researcher-Driven AI, we've condensed the entire quant + qual research process from weeks into days (sometimes hours!) for 50+ enterprise brands — including Amazon, T-Mobile, Mars, NASCAR, and more. We're on a mission to scale and democratize world-class research. From survey generation to stakeholder-ready reports, our platform is redefining how insights teams operate — and we need your help to push the limits of what's possible. Overview We're continuing to build out our NYC engineering team and are looking for exceptional builders who are resourceful, deeply technical, and thrive in high-ownership environments. As an early member of the team, you'll play a key role in shaping the core of our platform and contributing to a team that will scale to 20+ engineers over the next 18 months. You'll build and orchestrate AI agents, explore new UX paradigms, and work on some of the hardest problems in applied AI with meaningful ownership across the stack. Responsibilities | What you will own... Primary responsibilities of this role: • Own 0→1 and 1→N features across the stack, from design docs to building high-throughput data pipelines and scalable FastAPI services., • Architect and own the core agent orchestration engine, designing complex, multi‑agent LLM workflows (routing, tool‑use, memory, evaluation) with deterministic fallbacks, guardrails, and auditable actions required by enterprise users., • Build AI‑native, human‑in‑the‑loop UIs. Craft React/Next.js interfaces that let users collaborate safely with agents, with transparency and explainability by design., • Develop the "factory for the factory". Build our experimentation platform: CI/CD for prompts and agents, offline/online evals, drift detection, safety layers, and rollout controls., • Ship fast, safely. You'll instrument everything for reliability, write concise design docs, add robust tests, and build dashboards and alerts for features you launch., • Partner cross‑functionally with Product, AI, Design, CS; talk to customers and SMEs, and turn ambiguous problems into shipped product., • Obsess over performance, optimizing for latency across the system: caching, model selection, distillation, batching, vector search, and infrastructure efficiency (GPU/CPU)., • Operate what you build. This includes on‑call ownership, leading incident response, and driving learning through blameless postmortems., • Level-up the team around you. Mentor and collaborate with other engineers to help make the entire team better.This role is for you if..., • You're a 0 → 1 builder who thrives in ambiguity and has shipped products from scratch at a startup or in a hyper-growth phase. You've seen both - early-stage hustle and later-stage scale and know how to build for it., • You're a systems thinker with deep technical chops: you design clear architectures and write clean, tested Python and TypeScript., • You think like an owner: you spot problems, propose solutions, and build them without waiting for perfect specs. Your impact is measured in business outcomes., • You use AI as leverage. Tools like Cursor, Copilot, or Claude Code are integral to your workflow, helping you ship faster while maintaining a high standard for correctness., • You believe speed and quality aren't opposites and can articulate the tradeoffs you make., • You communicate crisply. You share your ideas effectively and thrive in tight feedback loops with product, design, and customers., • You've got grit: hard problems energize you, context switching doesn't scare you, and you're comfortable deleting code.Our Stack, • Frontend: React, Next.js, • Backend: Python, FastAPI, • Data/ML: MongoDB, S3, Redis; Pinecone, • Infra: AWS, Docker, Kubernetes; CI/CD with GitHub Actions., • Messaging: SQS; event‑driven pipelines.Required Skills & Experiences The successful candidate will be a high-ownership, product-minded engineer who combines strong full-stack fundamentals with experience building AI-native systems, capable of turning ambiguous problems into scalable, reliable features that drive real business impact. Required: • Experience with LLM/agent systems, evals, and prompt tooling; RAG, embeddings, vector dbs., • Deep knowledge of event‑driven systems, streaming, and workflow engines., • Expertise in observability (OpenTelemetry/Prometheus/Datadog), feature flagging, or A/B platforms., • Background in enterprise security and compliance (SOC 2, GDPR), • Bias to action: short specs, small PRs, daily deploys., • In-person collaboration: we're building the NYC hub together; whiteboards > long threads., • Are 1% better every day: We approach situations with a growth mindset and ask, "How can we make the business better?" and "What would it take?", • Play to win: We set audacious goals and push ourselves to achieve them with a bias towards action (When we see a need, we take initiative, and hold ourselves accountable to seeing it through). CCPA disclosure here.

Job Description About Syllo Syllo is on a mission to transform litigation. Our product is an AI-powered litigation workspace that enables lawyers and paralegals to safely harness the power of language models throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms in the country, and we are quickly expanding. By reducing the expense of litigation industry-wide, we aim to improve access to high-quality representation and promote the alignment of legal outcomes with merit. We're looking for a Back-End Engineer who's excited to build and scale systems that power intelligent data experiences. If you're passionate about clean architecture, reliable APIs, and high-performance infrastructure — and you love working in a dynamic startup environment — we'd love to meet you. The Responsibilities • Design, build, and maintain Syllo's backend systems and APIs to support our data platform., • Collaborate closely with front-end engineers, product managers, and data teams to deliver scalable, high-quality features., • Write clean, maintainable, and well-tested code., • Work on system design and architecture to improve performance, reliability, and scalability., • Integrate data sources and third-party tools as needed to enhance platform capabilities., • Participate in technical design discussions, peer code reviews, and continuous improvement initiatives. Qualifications • 6+ years of professional engineering experience., • Strong programming skills in Ruby or Python., • Experience developing APIs using frameworks such as Ruby on Rails, Flask, or Django., • Proficiency with relational databases, full-text search engines, and/or vector databases., • Familiarity with distributed systems and cloud technologies (e.g., GCP, Pub/Sub, Kafka)., • Excellent communication and organizational skills, with the ability to collaborate effectively across teams and functions. Nice-to-Have • Experience with Docker, Kubernetes, or other containerization tools., • Knowledge of CI/CD pipelines, testing frameworks, and deployment automation., • Understanding of authentication, security, and data privacy best practices., • Experience working in a fast-paced startup environment. United States - Remote Pay Range$160,000—$200,000 USD

Job DescriptionCompany Description For More Open Positions Visit us at: Our Mission WOONGJIN, Inc. is a rapidly growing team who provides a range of unique, exceptional, and enhanced services to our clients. We have a strong moral code that includes the service of goodness without expectations of reward. We are motivated by the sense of responsibility and servant leadership. Benefits • Medical Insurance, • Vision Insurance, • Dental Insurance, • 401(k), • Paid Sick hoursJob Description, • Design and develop algorithms for generative models using deep learning techniques, • Design and build LLM-powered applications for internal and/or customer-facing use cases, • Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems, • Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration, • Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate, • Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability, • Implement prompt engineering, structured outputs, tool calling, and model optimization strategies, • Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices, • Build monitoring, observability, and feedback loops for model and application performance in production, • Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems, • Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities, • Mentor other engineers and contribute to architecture, technical direction, and engineering best practicesQualifications Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field, • 5+ years of software engineering, machine/deep learning engineering, or applied AI experience, • 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production, • Strong programming skills in Python and experience with backend/API development, • Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design, • Experience in optimizing RAG pipelines using both structured and unstructured data, • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent, • Experience in generative AI techniques such as GANs, and VAEs, • Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search, • Experience with cloud platforms such as AWS, GCP, or Azure, • Experience with Docker, Kubernetes, CI/CD, and production deployment practices, • Strong understanding of software architecture, scalability, reliability, and distributed systems, • Experience building evaluation, testing, and monitoring for AI systems, • Strong communication skills and ability to work closely with technical and non-technical stakeholder Preferred Qualifications • Experience fine-tuning or adapting open-source LLMs, • Advanced knowledge of natural language processing for text generation tasks, • Experience with PyTorch, TensorFlow, JAX, or related ML frameworks, • Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar, • Experience building multi-agent systems or advanced orchestration workflows, • Experience with AI safety, guardrails, red-teaming, privacy, and governance, • Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems, • Experience in customer-facing or enterprise SaaS products, • Experience in semiconductor/manufacturing, retail and e-commerce sectors What Success Looks Like • Deliver production-ready GenAI features that improve user experience and business outcomes, • Build reliable and scalable AI systems with strong quality, latency, and cost performance, • Establish best practices for evaluation, observability, and responsible AI development, • Help define the company’s long-term Generative AI architecture and roadma Additional Information All your information will be kept confidential according to EEO guidelines. * NO C2C *

Job DescriptionApplied AI Engineer (AI-Native Marketplace) Location: New York City (on-site, relocation supported) Compensation: USD 170,000 – 230,000 + Equity Hiring: Up to 2 engineers Company: Confidential (represented by Worthland) About the Project Our client is a well-funded, AI-native startup building a real production marketplace in a space that has historically relied on manual workflows and human judgment. The company has achieved clear product–market fit, is growing rapidly with a lean team, and uses AI not as an add-on but as the core decision engine of the business. Their systems directly impact matching quality, speed, and operational efficiency at scale. This is a hands-on role for builders who want to ship AI systems that operate in messy, real-world conditions and materially move business metrics. The Role As an Applied AI Engineer, you will own end-to-end AI systems powering the marketplace: scoring, matching, ranking, recommendations, and internal automation. You will work directly with the founder and operations team. There is no separate ML platform team—you own the full loop, from problem definition through production iteration. This is not a research role and not an infra-only ML position. It is a product-focused, applied AI builder role. Role Split (Approximate) * ~60% Applied AI / ML: model selection, prompting, fine-tuning, evaluation, experimentation * ~40% Product & Engineering: backend services, APIs, data pipelines, product integration First 30 Days (What Success Looks Like) Week 1 * Develop a deep understanding of existing AI systems (scoring, matching, automation) * Identify where models perform well vs. where they fail in production * Partner with the ops team to understand manual overrides and edge cases * Align with the founder on the highest-leverage problems to solve first Weeks 2–4 * Ship meaningful improvements to scoring/matching models and related product features * Begin reducing manual ops load through smarter automation * Take ownership of the AI roadmap, using the founder as a thought partner—not a project manager Key ResponsibilitiesApplied AI & Decision Systems * Build and improve matching, scoring, and ranking systems that directly affect marketplace outcomes * Design explainable and calibratable AI outputs so users can understand and trust decisions * Compare new inputs against historical outcomes to surface meaningful signal * Iterate based on real-world feedback, not just offline metrics Automation & Internal Systems * Replace manual review steps with intelligent AI-driven workflows * Build feedback loops where human overrides improve model performance over time * Identify and surface stuck or anomalous cases requiring human attention Product-Facing AI Features * Generate structured summaries from unstructured data (documents, notes, transcripts) * Build retrieval-based assistants and role-specific AI tools * Ship features that are user-facing, measurable, and tightly integrated into the product Experimentation & Evaluation * Design evaluation frameworks that reflect real business impact, not just model accuracy * Implement experimentation and A/B testing to validate improvements * Make pragmatic tradeoffs (prompt vs. fine-tune, off-the-shelf vs. custom) RequirementsMust-Have * 4+ years of engineering experience with AI/LLM features shipped to production * Experience owning AI systems end-to-end in a real product environment * Hands-on experience with LLM APIs, embeddings, vector databases, and evaluation * Strong backend or full-stack engineering fundamentals * Comfort working with imperfect data and evolving requirements Strong Plus * Experience at an AI-native startup or as a founding / early engineer * Background in recommendation systems, matching, search, or automation * Product intuition and comfort making fast, high-impact decisions * Willingness to be hands-on rather than operating through layers of abstraction Not a Fit If You Primarily: * Work only on ML platforms or infrastructure without owning product features * Focus on research, publishing, or offline experimentation * Require clean datasets and mature infra before shipping * Have only built basic RAG demos as your main AI experience * Prefer large, highly structured organizations Why This Role * High ownership and direct impact on core business metrics * Close collaboration with the founder and decision-makers * AI-first product where models are central, not decorative * Competitive compensation, meaningful equity, and long-term upside Interview Process * Intro Call (30 minutes): High-level screening to assess role fit, hands-on AI experience, and mutual interest in the opportunity and company stage. * Technical Interview (60 minutes): Applied system design discussion focused on a real-world AI problem (e.g. matching, ranking, automation), evaluating practical decision-making and tradeoffs. * Behavioral Deep Dive (60 minutes): Review of past experiences, ownership mindset, and working style in high-autonomy, fast-moving environments. * On-Site (Full Day): Collaborative working session solving real problems with the team to assess technical depth, problem-solving approach, and collaboration in practice.

Job Description About impact.com impact.com is the world's leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L'Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results. Your Role at impact.com: We're seeking a Data Scientist to help build the next generation of recommendation systems powering our partnership automation platform. Our ecosystem connects a rich set of entities—advertisers, media publishers, creators, products, and consumers—and the relationships between them are where the real value lives. Your work will help surface the right partnerships, the right products, and the right content across this network at scale. You'll contribute to evolving our recommender stack toward a graph-based architecture leveraging semantic embeddings of entities and their relationships, applying cutting-edge techniques in representation learning, graph ML, and retrieval. The system needs to serve recommendations both in batch and real time, respond to dynamic user inputs, drive measurable value for end users across the platform, and remain reliable as the ecosystem grows. This role is hands-on and end-to-end. You'll own modeling and experimentation work for a defined area of the recommendation stack—from problem framing through productionization—in close partnership with Engineering, Product, MLOps, and Business Stakeholders. You're expected to bring (or actively develop) ML engineering chops so you can take a solution from prototype to production, and to be a relentless user of AI coding agents to multiply your output and accelerate iteration. What You'll Do: Core Responsibilities Multi-entity recommendations across the partnership graph Design, build, and evaluate recommendation models that operate across heterogeneous entities—advertisers, publishers, creators, products, and consumers—and the relationships between them. Frame problems in terms of the partnership graph and apply techniques appropriate to each surface, including candidate generation, ranking, reranking, and personalization. Graph-based modeling & semantic embeddings Contribute to evolving our architecture toward graph-based approaches: learn semantic embeddings of entities and relationships, apply graph neural networks or attention aware graph transformer models where they add value, and build representations that generalize across surfaces and use cases. Stay current with cutting-edge techniques in graph ML, representation learning, and modern recommender architectures, and bring relevant ideas into the platform. Batch and real-time serving Build models and pipelines that serve recommendations in both batch and real-time contexts. Partner with Engineering on retrieval infrastructure, vector search, feature stores, and low-latency serving patterns. Make pragmatic tradeoffs between model sophistication, latency, cost, and freshness based on the surface and use case. End-to-end ML delivery & ML engineering Own the full lifecycle of your work: data and feature design, model development, evaluation, launch, monitoring, and iteration. Build production-grade pipelines, write code that other engineers can extend, and partner with MLOps on reproducibility, observability, and reliability. Use AI coding agents aggressively to accelerate prototyping, refactoring, debugging, and shipping—we expect this to be a core part of how you work, not an occasional aid. Experimentation & measurement Design offline evaluation (offline replay, counterfactual evaluation, holdout sets) and online experiments (A/B tests, holdouts, interleaving) to quantify model impact. Apply appropriate statistical methods, recognize common pitfalls in recommender evaluation (position bias, feedback loops, selection effects), and translate results into clear recommendations for product and engineering partners. Cross-functional collaboration Work closely with Product, Engineering, and Business Stakeholders to translate platform goals into measurable model outcomes. Communicate findings, tradeoffs, and recommendations clearly to both technical and non-technical audiences. Document your work so that models, features, and decisions are understandable and reproducible by others. What You Bring: • 3+ years of experience in data science / applied ML, with a track record of shipping production models that delivered measurable user or business impact., • Strong Python and SQL skills; experience working with large-scale data and distributed compute (Spark/Databricks or equivalent)., • Hands-on experience building recommendation or ranking systems—candidate generation, learning-to-rank, retrieval and reranking, or implicit feedback modeling., • Experience with embeddings and representation learning for users, items, content, or other entities., • ML engineering capability (or strong willingness and demonstrated ability to develop it): you can build, ship, and maintain production pipelines—not just prototypes in notebooks., • Strong experimentation skills: designing and analyzing A/B tests, interpreting results, and communicating findings to stakeholders., • Relentless user of AI coding agents in your day-to-day workflow, with a clear sense of where they accelerate you and where they don't., • Insatiable curiosity about new techniques, architectures, and tools—and a track record of teaching yourself things quickly. You read papers, try new tools, and bring ideas back to the team., • Strong problem-solving instincts and the ability to operate with growing autonomy in ambiguous, evolving spaces.Preferred / Nice to have, • Experience with graph-based ML: graph neural networks (KGAT, transformers or similar), graph-aware retrieval, or knowledge graph embeddings., • Experience with modern deep learning recommender architectures (two-tower, sequence/transformer-based recommenders, multi-task ranking)., • Familiarity with vector search and vector databases (FAISS, ScaNN, Vespa, Milvus, or similar) and approximate nearest neighbor methods., • Experience with real-time ML serving, feature stores (Feast, Tecton, or equivalent), and low-latency inference patterns., • Exposure to contextual bandits, reinforcement learning, or off-policy evaluation in recommendation settings., • Familiarity with PyTorch/TensorFlow and PyTorch Geometric / DGL for graph workloads., • Familiarity with GCP (Vertex AI, BigQuery, Cloud Run) and/or mature MLOps practices (CI/CD for ML, monitoring, drift detection)., • Experience in adtech, martech, e-commerce, or two-sided/multi-sided marketplace recommendations.What Sets You Apart, • You think in terms of user and business outcomes, not just model metrics, and you connect modeling choices to real value delivered through the platform., • You're rigorous about measurement but pragmatic about shipping—able to deliver MVPs and iteratively evolve them into durable production systems., • You're a relentless learner. New papers, new tools, new architectures—you find them, try them, and figure out where they fit. You don't wait to be told what to learn., • You use AI coding agents like a power user: they're a force multiplier in your hands, not a crutch., • You have engineering instincts—you care about code quality, system design, and operability, not just model performance., • You're comfortable with messy data, noisy feedback, edge cases, and ambiguous problem spaces, and you excel at iterative improvement. *This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Benefits and Perks: At impact.com, we believe that when you're happy and fulfilled, you do your best work. That's why we've built a benefits package that supports your well-being, growth, and work-life balance. • Medical, Dental, and Vision insurance, • Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled, • Flexible spending accounts and 401(k), • Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life., • Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health., • A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval., • Investing in Your Growth: We're committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses., • Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver., • Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors. #LI_NewYork

Job Description Location: New York, NY Our client is a distinguished provider of legal services on a global scale. As an Innovation AI Developer, you will serve as a key member of the client’s Innovation Engineering team, responsible for designing and implementing intelligent, secure, and scalable AI applications to enhance the delivery of legal services and optimize business operations. In this capacity, you will collaborate closely with attorneys, business leaders, data scientists, and infrastructure teams to translate complex legal and operational needs into effective AI solutions with measurable outcomes. You will be involved in the entire AI lifecycle—from initial use case identification through production deployment and system monitoring—utilizing large language models (LLMs), retrieval-augmented generation (RAG), traditional machine learning approaches, and modern cloud architectures to advance efficiency, quality, and informed decision-making. This position offers the opportunity to develop enterprise-level AI capabilities at one of the world’s premier law firms, operating at the forefront of advanced engineering and impactful legal practice. The firm is committed to upholding rigorous performance standards and fostering a culture oriented toward growth. Individuals demonstrating initiative and dedication will be afforded opportunities for increased responsibilities and long-term career advancement within the organization. Must be a U.S. Citizen or Green Card holder - our client cannot accept work visas and/or sponsorships at this time Desired Qualifications and Experience: · Bachelor’s degree in computer science or a related field preferred. · 7+ years of experience in professional services, legal, or technical environments, with demonstrated hands-on experience building and deploying AI applications. · AI Engineering Expertise – Strong Python development skills and experience designing and implementing RAG pipelines, working with vector databases (e.g., Pinecone), and building AI agents and multi-service AI architectures—particularly within Azure environments. · Cloud & DevOps Proficiency – Familiarity with Azure services (e.g., Cognitive Search, Cosmos DB, AI Studio), as well as Docker, Kubernetes, and CI/CD practices that support scalable, production-ready deployments. · Experience designing and maintaining LLM evaluation frameworks (e.g., Promptfoo, OpenAI Evals, LangSmith) and integrating structured and unstructured data sources into AI systems. · Experience operating within environments that require strict adherence to security, privacy, and governance standards for sensitive data. · Business Acumen & Communication – Proven ability to conduct stakeholder discovery, quantify return on investment (ROI), and translate ambiguous challenges into clearly defined AI requirements. · Strong communication skills with the ability to explain complex technical concepts to non-technical audiences. · Legal Domain Exposure (Preferred) – Experience supporting legal use cases such as due diligence, contract review, or legal research, and prior law firm experience. Summary of Responsibilities: · AI Solution Architecture & Development – Collaborate with legal and business stakeholders to identify high-value AI use cases, define measurable success criteria (e.g., efficiency, quality, risk reduction), and architect scalable solutions using Python and modern AI frameworks such as OpenAI, Azure OpenAI, Hugging Face, LangChain, and LangFlow. · Retrieval-Augmented Generation (RAG) & Intelligent Systems – Design, build, and maintain RAG pipelines using vector databases and knowledge graph solutions. Develop AI agents that automate multi-step workflows and enable sophisticated task orchestration. · Create reusable libraries, patterns, and documentation that support long-term innovation and maintainability across the firm’s AI ecosystem. · Design and maintain LLM evaluation frameworks to measure accuracy, robustness, safety, and alignment to use-case objectives. Ensure AI systems meet firm security, privacy, and governance standards. · Support continuous integration and continuous delivery (CI/CD) workflows, containerization (Docker), and orchestration (Kubernetes) to ensure production readiness. Partner with infrastructure and security teams to support hybrid cloud and on-premise deployments in sensitive data environments. · Serve as a subject matter resource for attorneys and business teams, advising on prompt engineering, model selection, and architecture decisions. Support pilot implementations, user training, and feedback loops to drive adoption and measurable impact. · Evaluate new tools, open-source libraries, and vendor platforms to inform firm AI strategy. Contribute to internal education and thought leadership on AI best practices. How to Apply: Our client has hired us to help facilitate the initial interview and recruiting process. Please attach your current version of your resume and make sure you complete our initial pre-screening questions that will be used for determining which applicants will be considered at this time. Thank you for your interest. Company DescriptionWe Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!We Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!

Job Description We build AI agents that actually work in enterprise environments — not prototypes, not demos. We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that are model-agnostic and built to last. You'll be deployed on client engagements as the lead technical architect and builder of agentic systems running in AWS, OCI, and Azure. You'll work directly with client stakeholders, translate complex requirements into working systems, and leave behind infrastructure clients can operate and extend. You'll also help Trilagen productize our delivery approach as we scale the practice. If you've only ever built agents that run on your laptop, this isn't the role. If you've shipped agentic systems into production cloud environments and know exactly what breaks and why — we want to talk. What you'll own Full-stack agent development You design and build the entire application — not just the AI layer. This means a React or Next.js frontend with streaming, real-time agent UX; a Python or Node.js backend that orchestrates agent logic, manages state, and exposes clean APIs; and containerized, cloud-deployed services that operations teams can actually run. You own the repo, the CI/CD pipeline, the deployment, and the runbook. Multi-cloud deployment Production agent systems on all three major clouds: AWS (Lambda, ECS/Fargate, Bedrock, API Gateway), Oracle OCI (OKE, Functions, AI Services), and Azure (AKS, Azure OpenAI Service, Azure Functions). You understand the tradeoffs between platforms and can advise clients on where to run what and why. LLM integration and model strategy You have deep, hands-on experience with the leading LLM providers and their APIs — Anthropic Claude (Messages API, tool use, streaming, context management), OpenAI (GPT-4o, Assistants API, function calling), and Google Gemini (Gemini Pro/Flash, Vertex AI). You architect model-agnostic integration layers so clients aren't locked in, and you know how to select, swap, and benchmark models for specific agent tasks. Agentic architecture You understand how to design systems that do real multi-step work: tool use and function calling patterns, ReAct and plan-and-execute loops, agent-to-agent orchestration and handoffs, human-in-the-loop checkpoints, retry and failure recovery strategies, and cost/latency optimization across long-running agent workflows. Frameworks like LangGraph, CrewAI, AutoGen, and the Model Context Protocol (MCP) are tools in your toolbox, not the ceiling of your knowledge. Memory and context layer You've designed and implemented memory architectures for production agents: short-term conversational context, long-term persistent memory, RAG pipelines with vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and identity layer This is non-negotiable for our client base. You build the security envelope around every agent system you ship: OAuth 2.0 / OIDC authentication flows, API key lifecycle management, role-based access control enforced within agent workflows, secrets management (AWS Secrets Manager, Azure Key Vault, OCI Vault), audit logging for agent actions, prompt injection defense, and data residency controls. Familiarity with Okta or SailPoint ISC is a direct advantage on our engagements. Requirements • 4+ years of software engineering experience with at least 2 years building and shipping LLM-powered or agentic applications in production cloud environments, • Hands-on depth with at least two of the three major LLM providers: Anthropic Claude, OpenAI, and Google Gemini — at the API level, not just via wrappers, • Full-stack proficiency: Python (FastAPI, Flask, or similar) backend, React or Next.js frontend, REST and WebSocket API design, • Production experience on at least two of: AWS, Azure, OCI — with real deployments, not sandbox accounts, • Demonstrated ability to design and implement agent memory and retrieval systems using vector databases and RAG, • Strong command of AI security practices: auth, RBAC, secrets management, audit logging, and prompt-level safeguards, • Experience with all three LLM providers (Anthropic, OpenAI, Gemini) and model-agnostic orchestration patterns, • Okta and/or SailPoint ISC integration experience Benefits: • 401K, • Health Insurance, • Dental Insurance, • Paid Time Off, • Paid Sick Leave

Job DescriptionCompany Description Accel Learning is a New Jersey-based tutoring and test-prep center serving 3,000+ students across K–12 and beyond. We prepare students for some of the most competitive exams in the country - SAT, ACT, ISEE, BCA, SSAT, HSPT, GRE, GMAT, Regents, NJSLA, OLSAT, SCAT, TerraNova, Praxis, PSEG, Math Olympiad, AMC, MathCounts, and more. Our Mission: Make rigorous, personalized learning accessible. Today our instructors build question banks manually in WordPress. We're changing that by building an AI-powered question generation engine that creates exam-ready, curriculum-aligned questions at scale. Job Description You will architect and implement the core AI pipeline that powers Accel's test creation system. • Work closely with the founder to design and build an AI-powered content generation system from the ground up. You'll contribute to meaningful parts of the product end-to-end from how the system ingests and understands source material, to how it produces and validates outputs, to how instructors interact with and review what the system generates., • On the engineering side, you'll build and iterate on LLM-driven pipelines, work with retrieval and embedding techniques to ground outputs in real source material and develop backend services and APIs that tie everything together., • Beyond pure coding, you'll be expected to think about output quality and building evaluation steps, catching failure modes, and improving the system based on real instructor feedback. You'll research new tools and techniques as the AI space evolves and bring relevant ideas directly into the product., • Strong foundation in software engineering: data structures, APIs, system design, • Proficiency in Python (primary language for AI/ML pipeline work), • Experience with REST APIs and at least one database (PostgreSQL preferred), • Ability to work independently, ask sharp questions, and iterate fast, • Strong debugging and problem-solving instincts, • Demonstrated side projects or shipped code (GitHub portfolio required), • Genuine interest in AI systems and education technology, • Direct experience with LLM APIs: OpenAI, Anthropic Claude, or Google Gemini, • Experience with NLP pipelines: text chunking, tokenization, semantic search, • Knowledge of LaTeX syntax and math rendering libraries (MathJax, KaTeX), • Experience with image generation APIs or SVG programmatic generation, • Familiarity with AI evaluation frameworks or automated test harnesses for LLM outputs, • Cloud platform experience: AWS, GCP, or Vercel for deployment, • Experience with job queues: Celery, Bull, or similar, • Exposure to educational content standards or psychometrics is a bonus Additional Information All your information will be kept confidential according to EEO guidelines.

Job DescriptionA little about us… Knit is the AI-native consumer research platform helping brands automate and accelerate primary research. With our Researcher-Driven AI, we've condensed the entire quant + qual research process from weeks into days (sometimes hours!) for 50+ enterprise brands — including Amazon, T-Mobile, Mars, NASCAR, and more. We're on a mission to scale and democratize world-class research. From survey generation to stakeholder-ready reports, our platform is redefining how insights teams operate — and we need your help to push the limits of what's possible. Overview We're continuing to build out our NYC engineering team and are looking for exceptional builders who are resourceful, deeply technical, and thrive in high-ownership environments. As an early member of the team, you'll play a key role in shaping the core of our platform and contributing to a team that will scale to 20+ engineers over the next 18 months. You'll build and orchestrate AI agents, explore new UX paradigms, and work on some of the hardest problems in applied AI with meaningful ownership across the stack. Responsibilities | What you will own... Primary responsibilities of this role: • Own 0→1 and 1→N features across the stack, from design docs to building high-throughput data pipelines and scalable FastAPI services., • Architect and own the core agent orchestration engine, designing complex, multi‑agent LLM workflows (routing, tool‑use, memory, evaluation) with deterministic fallbacks, guardrails, and auditable actions required by enterprise users., • Build AI‑native, human‑in‑the‑loop UIs. Craft React/Next.js interfaces that let users collaborate safely with agents, with transparency and explainability by design., • Develop the "factory for the factory". Build our experimentation platform: CI/CD for prompts and agents, offline/online evals, drift detection, safety layers, and rollout controls., • Ship fast, safely. You'll instrument everything for reliability, write concise design docs, add robust tests, and build dashboards and alerts for features you launch., • Partner cross‑functionally with Product, AI, Design, CS; talk to customers and SMEs, and turn ambiguous problems into shipped product., • Obsess over performance, optimizing for latency across the system: caching, model selection, distillation, batching, vector search, and infrastructure efficiency (GPU/CPU)., • Operate what you build. This includes on‑call ownership, leading incident response, and driving learning through blameless postmortems.This role is for you if..., • You're a 0 → 1 builder who thrives in ambiguity and has shipped products from scratch at a startup or in a hyper-growth phase. You've seen both - early-stage hustle and later-stage scale and know how to build for it., • You're a systems thinker with deep technical chops: you design clear architectures and write clean, tested Python and TypeScript., • You think like an owner: you spot problems, propose solutions, and build them without waiting for perfect specs. Your impact is measured in business outcomes., • You use AI as leverage. Tools like Cursor, Copilot, or Claude Code are integral to your workflow, helping you ship faster while maintaining a high standard for correctness., • You believe speed and quality aren't opposites and can articulate the tradeoffs you make., • You communicate crisply. You share your ideas effectively and thrive in tight feedback loops with product, design, and customers., • You've got grit: hard problems energize you, context switching doesn't scare you, and you're comfortable deleting code.Our Stack, • Frontend: React, Next.js, • Backend: Python, FastAPI, • Data/ML: MongoDB, S3, Redis; Pinecone, • Infra: AWS, Docker, Kubernetes; CI/CD with GitHub Actions., • Messaging: SQS; event‑driven pipelines.Required Skills & Experiences The successful candidate will be a high-ownership, product-minded engineer who combines strong full-stack fundamentals with experience building AI-native systems, capable of turning ambiguous problems into scalable, reliable features that drive real business impact. Required: • Experience with LLM/agent systems, evals, and prompt tooling; RAG, embeddings, vector dbs., • Deep knowledge of event‑driven systems, streaming, and workflow engines., • Expertise in observability (OpenTelemetry/Prometheus/Datadog), feature flagging, or A/B platforms., • Background in enterprise security and compliance (SOC 2, GDPR), • Bias to action: short specs, small PRs, daily deploys., • In-person collaboration: we're building the NYC hub together; whiteboards > long threads., • Are 1% better every day: We approach situations with a growth mindset and ask, "How can we make the business better?" and "What would it take?", • Play to win: We set audacious goals and push ourselves to achieve them with a bias towards action (When we see a need, we take initiative, and hold ourselves accountable to seeing it through). CCPA disclosure here.

Job DescriptionWhat We Do Gecko Robotics is helping the world’s most important organizations ensure the availability, reliability, and sustainability of critical infrastructure. Gecko's complete and connected solutions combine wall-climbing robots, industry-leading sensors, and an AI-powered data platform to provide customers with a unique window into the current and future health of their physical assets. This enables real-time decision making to increase the efficiency and safety of operations, promote mission readiness, and protect the environment and civilization from the effects of infrastructure failure. Role at a Glance As an AI Focused Software Engineer, you will build and evolve the data backbone of an agentic AI system leveraging document intelligence, time-series IoT data, and customer activity logs. This is a highly hands-on, end-to-end role for someone who thrives in early-stage ambiguity, is comfortable working close to models and customers, and wants to directly shape how data-driven agents are built and deployed for production. This role will initially focus on the power industry, where your work will directly support the reliable operation of power plants used by millions of people every day. What you will do You will design, implement, and agentic systems across the full lifecycle, from data ingestion and processing to building and tuning models for use by customers in the real world. You’ll work directly with customers and internal stakeholders to understand real problems, translate them into technical solutions, and iterate quickly. You’ll build agentic workflows, document processing pipelines, and sensor data ingestion. You’ll contribute to feature engineering and model experimentation when needed, and own systems in production. You’ll make pragmatic architectural decisions, improve reliability over time, and help define best practices as the team and product scale. Technologies We Use * Python, React * Cloud-native data and GenAI tooling (GCP, VertexAI, etc) * Streaming and messaging systems * Distributed processing frameworks * Data warehouses, lakes, and object storage * Time-series and NoSQL databases * ML and AI tooling (feature stores, vector databases, model pipelines) * Docker, Kubernetes, and infrastructure-as-code tools About You You’re a builder who likes owning problems end to end—from understanding customer needs to shipping and maintaining production systems. You’re comfortable crossing boundaries between software engineering, ML, and backend work, and you’re energized by fast feedback loops and real-world impact. You prefer pragmatic solutions over perfect ones, communicate clearly with technical and non-technical stakeholders, and enjoy helping shape both the product and the engineering culture. Required Skills * 7+ years of experience in software engineering, backend engineering, or adjacent roles * Strong Python skills, proficient with ML packages and distributed backends * Experience building production data pipelines and systems from scratch * Comfort working with both structured and unstructured data * Experience operating systems in production and owning reliability * Ability to work directly with customers or end users to understand requirements * Strong problem-solving skills in ambiguous, fast-moving environments Preferred Skills * Experience with agentic AI systems or similar orchestration frameworks for enterprise-grade reasoning and/or automation * Experience with document processing, NLP, or vector search * Experience with time-series or IoT data * Startup or early-stage product experience * Experience making architectural tradeoffs under real-world constraints Who We Are At Gecko, our people are our greatest investment. In addition to competitive compensation packages, we offer company equity, 401(k) matching, gender-neutral parental leave, full medical, dental, and vision insurance, mental health, ongoing professional development, family planning assistance, and flexible paid time off. Gecko values collaboration, innovation, and partnership, and we believe we do our best work when we're together in person. We’re an office-first culture but understand that sometimes you may need to work from home. Many people are in the office five days a week, others need a bit more flexibility. Ultimately, we care about the outcomes we achieve - and creating a culture of autonomy and trust that enables that impact. Gecko is committed to creating a culture of inclusion and belonging, and we are proud to be an equal opportunity employer. We believe it is our collective responsibility to uphold these values and encourage candidates from all backgrounds to join us in our mission to protect today’s infrastructure and give form to tomorrow’s. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, veteran status, age, or any other protected characteristic per federal, state, or local law. If you are passionate about what you do and want to use your talents to support our critical mission, we’d love to hear from you. Compensation Range: $140K - $245K

Job Description Capgemini is at the forefront of Generative AI innovation, helping Financial Services clients industrialize GenAI and Agentic AI platforms at enterprise scale. We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS‑ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments. In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production‑grade, governed, multi‑agent systems. You will apply leading GenAI frameworks and LLM platforms — including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases—while operating across the full Agentic SDLC. P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role. We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers. Requirements Client Advisory & Product Vision • Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology., • Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human‑in‑the‑loop checkpoints, and escalation logic., • Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions., • Design and implement multi‑agent architectures using modern GenAI tooling, including:, • Planner, executor, reviewer/critic, and supervisor agents, • Tool‑calling and function‑calling agents, • Memory‑enabled agents (conversation, semantic, episodic, and structured memory), • Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow., • Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control., • Design agent interaction patterns such as hierarchical agents, collaborating agents, and event‑driven agent workflows., • Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:, • Agent design specifications and behavior contracts, • Prompt, policy, and tool versioning, • Simulation environments and offline evaluation, • Automated testing of agent flows and guardrails, • Controlled rollout, telemetry‑driven optimization, and continuous learning, • Build production‑grade AI services primarily using Python, integrating:, • LLM providers such as Anthropic (Claude), OpenAI, and open‑source models, • Retrieval‑Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate), • Implement CI/CD pipelines for agent code, prompts, and policies., • Implement agent observability including tracing, decision logging, tool usage, and failure analysis., • Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring., • Design feedback loops incorporating human‑in‑the‑loop review and reinforcement., • Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:, • Auditability and traceability of agent decisions, • Model and prompt explainability, • Data privacy and security controls, • Resilience and fail‑safe mechanisms, • Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures., • Provide technical leadership and mentorship to consulting delivery teams., • Contribute to internal GenAI accelerators, agent frameworks, and reusable assets., • Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures. This position comes with competitive compensation and benefits package: • Competitive salary and performance-based bonuses, • Comprehensive benefits package, • Career development and training opportunities, • Flexible work arrangements (remote and/or office-based), • Dynamic and inclusive work culture within a globally known group, • Private Health Insurance, • Retirement Benefits, • Paid Time Off, • Training & Development, • *Note: Benefits differ based on employee level About Capgemini Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 420,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group €22.5 billion in revenues in 2025.

Job Description Location: New York, NY Our client is a distinguished global provider of legal services. This is a full-time, direct hire onsite role requiring US Citizenship or Green Card. We are seeking a Legal Practice Technology Data Scientist. This position can be in San Francisco, Los Angeles, Chicago, or New York – relocation assistance is not offered. If you have spent your career in eDiscovery and litigation support and are ready to apply that foundation, along with a broader technical skill set, to a wider scope of work, this could be the role for you. Data Scientists sit within a group of discovery, data management, and AI specialists dedicated to designing and executing client-focused workflows on some of the most complex matters in our industry. You will report to the Associate Director of Technical Operations. The role is hands-on and client-facing; more than half of your time will be spent directly embedded in active matters. This position sits within the firm’s Innovation Program. Our client upholds strict performance standards and fosters a culture focused on continuous growth. Individuals who exhibit initiative and dedication will be offered opportunities for increased responsibilities and long-term professional advancement within the organization. Must be a U.S. Citizen or Green Card holder – sponsorship is not available Desired Qualifications and Experience: • Bachelor’s degree, • 3+ years of experience in a law firm, legal services, or professional services organization with significant experience working in a team environment., • Ability to translate complex concepts into client-friendly language., • Highly analytical with strong problem-solving skills and the ability to translate ambiguous problems into structured solutions., • Knowledge of statistical analysis and data modeling., • Demonstrated hands-on experience with Relativity custom development. Deep knowledge in eDiscovery-focused data processing, structured analytics, and related troubleshooting., • Expert-level proficiency in Microsoft Excel, including VBA development, Power Query, complex formula construction, advanced data modeling, and chart design., • Experience in creating data visualizations with hands-on proficiency in tools such as Plotly, Tableau, and Microsoft Power BI., • Strong Python skills for data analysis, statistical modeling, and AI/ML prototyping (e.g., pandas, PyTorch, TensorFlow); advanced SQL proficiency; experience building data pipelines., • Proficiency in front-end web technologies including JavaScript, HTML, and CSS, with the ability to develop interactive web-based tools and dashboards., • Hands-on experience with AI platforms and tools (e.g., OpenAI, Microsoft Azure OpenAI, Hugging Face, LangFlow, LangChain), including practical implementation of RAG pipelines, vector databases, and knowledge graph construction., • General knowledge of social network analysis, natural language processing, classification algorithms, and image processing., • Familiarity with git, svn, JIRA, or other version control technologies., • Familiarity with hardware platforms (e.g., CPUs, GPUs, FPGAs)., • Familiarity with leading legal technology platforms is preferred (docketing systems, document management systems, case management systems, eDiscovery, data collection and web capture solutions)., • Experience evaluating LLM output quality through benchmarking, precision, recall, and extraction accuracy assessment is preferred. Summary of Responsibilities: Coordination and Execution of In-house Solution Development. You will support the collection of requirements and the design and building of in-house solutions. You will consult with case teams on data strategies and execute rapid solution development including custom scripting, data management, database development, and visualization design. You will complete requests requiring advanced technologies such as document layout analysis, LLM-based information extraction, semantic chunking, and entity recognition, while maintaining comprehensive documentation throughout. Data Project Service Delivery. You will support matter-specific needs as a subject matter resource, analyzing and troubleshooting data processing and analytics issues. You will develop custom eDiscovery workflows and execute data-heavy, data-modeling projects that require creative problem-solving and technical depth. Department Initiatives. You will work closely with other data science teams and Legal Practice Technology (“LPT”) leadership to evaluate and test internal solutions and emerging technology. You will serve as a go-to resource for technical knowledge in AI, contributing your expertise to the team’s continuous advancement of its capabilities. How to Apply: Our client has hired us to help facilitate the initial interview and recruiting process. Please attach your current version of your resume and make sure you complete our initial pre-screening questions that will be used for determining which applicants will be considered at this time. Thank you for your interest. Company DescriptionWe Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!We Place People is a premiere Executive Search Firm working with leading companies nationwide. We have a direct relationship with our clients and a 95% hire rate! We differentiate ourselves from other firms & work closely with our candidates throughout the interview process. WE PLACE PEOPLE is what we do best!

Job Description Company Overview With an annual budget of $2.3 billion and more than 7,000 employees throughout the five boroughs, the New York City Department of Health and Mental Hygiene (NYC Health Department) is one of the largest public health agencies in the world, serving 8 million New Yorkers from diverse ethnic and cultural backgrounds. We're tackling a broad range of public health issues with innovative policies and programs and getting exceptional results, but our work is never finished. The breadth of our innovative programs provides the widest range of choices for every member of our team. With grant funds from the Centers for Disease Control and Prevention (CDC), the NYC Health Department is undertaking an initiative to prevent, prepare for, and respond to the expanding multistate outbreak of Influenza A/H5N1 and strengthen readiness for any respiratory disease threat with the potential to result in large, disruptive outbreaks to communities. The selected candidate will be an employee of Public Health Solutions, a nonprofit organization which is the fiscal and administrative manager of the grant but will work be supervised by the NYC Health Department. This is a grant-funded position ending in January 2027 The Division of Disease Control performs identification, surveillance, treatment, control and prevention of 90+ infectious diseases. It is one of the largest Divisions at the Health Department with seven bureaus including the Bureau of Communicable Diseases. The Bureau of Communicable Diseases is responsible for the surveillance, prevention, and control of over 70 infectious diseases, including foodborne, waterborne, respiratory, zoonotic and vector-borne diseases. Within the Bureau of Communicable Diseases, the Zoonotic and Vector-borne Disease Unit conducts surveillance and epidemiologic investigations for zoonotic and vector-borne diseases, and diseases in animals of potential public health concern (e.g., rabies, tularemia, anthrax, and avian influenza). Much of the unit’s work is conducted in collaboration with partners within and outside the Health Department. Job Description The NYC Health Department has an opening for an avian and novel influenza project coordinator. This position will serve as primary support for epidemiologic investigations for avian influenza/novel influenza viruses in NYC, develop protocols, and summarize data. They will have experience in epidemiology and data management and analysis and will participate in a wide range of activities. They will report to the Bureau of Communicable Disease (BCD) Zoonotic and Vector-borne Disease Unit Animal Health Team Lead, and will collaborate with the Disease Investigation Unit as well as Respiratory Pathogens Unit. Duties: • Oversee contact investigations (people and pets) related to avian influenza detections in animals, • Develop and maintain protocols related to avian and novel influenza for contact tracers, on-call physicians, and BCD staff including questionnaires, data entry tools, and trainings, • Conduct trainings for interns and rapid response teams on case and contact investigations and data entry, • Conduct routine and ad hoc analyses and prepare summaries of surveillance data, including analyses to identify clusters, or changes in epidemiologic trends, • Participate in outbreak investigations and as needed special epi projects on avian and novel influenza viruses, • Collaborate with outreach and health education staff to provide input for initiatives related to avian influenza and respiratory diseases, as well as a variety of diseases and conditions managed by the Bureau of Communicable Disease including foodborne, waterborne, zoonotic and vector-borne associated diseases, • Participate in development and maintenance of presentations to internal and external audiences, • Participate as needed on other animal disease investigations, • Graduate degree in field of public health, • Previous experience working in fields related to public health., • Experience in infectious disease epidemiology, • Ability to work well with others, • Experience with conducting interviews with health care providers, contacts and case patients., • Ability to effectively work independently as well as collaboratively and effectively on an interdisciplinary team, • Excellent communication (verbal & written) and interpersonal skills., • Desire to grow professionally, develop new skills and willingness to work outside of comfort zone., • Experience working with the public health sector and coordinating projects involving multiple stakeholders., • Ability to prioritize and work in fast-paced environment with hard deadlines., • Hybrid Work Schedule., • Generous Paid Time Off and Holidays., • An attractive and comprehensive benefits package including Medical, Dental and Vision., • Flexible Spending Accounts and Commuter Benefits., • Company Paid Life Insurance and Disability Coverage., • 403 (b) + employer matching and discretionary company contributions., • College Savings Plan., • This is a temporary grant-funded position ending January 2027, • This individual must reside in the tri-state area (NY, NJ, CT) by their confirmed start date., • Preference may be given to individuals residing in New York City (5 boroughs) or surrounding New York State counties. We look forward to learning more about you! PHS is proud to be an equal opportunity employer and encourages applications from women, people of color, persons with disabilities, LGBTQIA+ individuals, and veterans. Monday-Friday 35 Hours Per Week

Job Description Pactiv Evergreen is now a part of Novolex. Novolex is a leading manufacturer of food, beverage, and specialty packaging that supports multiple industries, including foodservice, restaurant delivery and carryout, food processing, grocery and retail, and industrial sectors. Our innovative product portfolio is designed to meet the diverse needs of businesses worldwide and the millions of customers they serve. Through continuous investment in research and development, we are committed to engineering more sustainable choices for the future. Our extensive manufacturing network spans North America and Europe, including two world-class plastic film recycling centers. Discover more about Novolex, our 20,000+ family members and our commitment to innovation and sustainability at . Our Social Responsibility platform features a robust, employee-led Give Back program, which includes a matching gifts plan, community grants initiative, and our annual Company-wide Month of Action campaign. With each of these initiatives, our employees are empowered and equipped to give back to their communities and support the non-profits important to them and their families. Through our Give Back program, we own our commitment to Social Responsibility and live our purpose of Packaging a Better Future. Job Description This position provides support for the reliability of all automation and control systems throughout the facility. The individual will work closely with all plant personnel to perform tests, diagnostics, repairs, improvements and upgrades to all equipment, instrumentation, process and procedures. Responsibilities: ● Drive a zero EHS incident culture, support and participate in incident investigations to determine root cause and identify preventive actions, correct unsafe conditions and acts immediately, and use every incident or near miss as a teaching moment for others ● Monitor, adjust, calibrate and repair manufacturing equipment, instruments, fixtures, etc. ● Conduct in-depth PLC, HMI, motor and drive troubleshooting and provide effective solutions – Allen Bradley required with at least one other manufacturer (i.e. Mitsubishi, Schneider, GE, Opto 22, etc.) ● Read and modify PLC ladder diagrams ● Perform electrical and electronic installations and modifications including drives and programming controllers ● Working knowledge of AC vector and servo drive technology. ● Understand in-depth electric circuitry, electronics and electromechanical concepts - AC and DC, Sinking / Sourcing, Analog, etc. ● Troubleshoot and maintain Fanuc robotic automation. (Palletizers, Case erectors, Pick and Place) ● Basic understanding of hydraulics, pneumatics and mechanical concepts ● Basic understanding of PC components ● Interpret all levels of drawings, wiring diagrams, schematics, specifications, etc. Knowledge of CAD system (i.e. AutoCAD, Vizio, etc.) ● Stay up to date with the latest state-of-the-art automation and control techniques ● Utilize problem solving techniques including PDCA to solve problems to root cause, implement actions that prevent reoccurrence, improve operations, etc. ● Supply higher level technical assistance to plant shift electrician team ● Provide training to all levels of the organization ● Ability to supervise contractors to minimize scheduled and unscheduled downtimes ● Maintain and manage the engineering department technical procedures, manuals and drawings, including records of as-built equipment and process changes ● Occasional need to work flexible hours. May include weekend and/or holiday work, subject to call-ins Qualifications: ● High school graduate or equivalent required ● Apprenticeship or equivalent training ● Associate’s degree in maintenance or industrial technology preferred ● Minimum five years of industrial maintenance experience with extensive automation and controls work ● Proficient in computer applications including Microsoft applications, Outlook, SAP, etc. ● Knowledge OSHA Electrical Standards, National Electric Code (NEC) ● Strong troubleshooting skills and logic to solve problems to root cause ● Proactive and self-motivated to work effectively with minimal supervision ● Good written and verbal communication skills ● Ability to make decisions under time constraints and tight deadlines ● Able to interact with other associates in a team-oriented environment Pactiv Evergreen is committed to a diverse and inclusive workforce. Pactiv Evergreen is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, sex (including pregnancy), sexual orientation, religion, creed, age national origin, physical or mental disability, genetic information, gender identity and/or expression, marital status, veteran status or other characteristics or statuses protected by law. For individuals with disabilities who would like to request an accommodation, please call (847) 482-4320 or email . All information will be kept confidential according to EEO guidelines and applicable laws. You should be proficient in: • Creating Preventive Maintenance Plans, • Mechanical Troubleshooting Skills, • Electrical Installation, • Electrical Troubleshooting, • Electrical Repair, • Pneumatics Troubleshooting, • Programmable Logic Controller (PLC) (Allen Bradley)

Job Description Do you want to empower organizations to build smarter compensation strategies while ensuring fair pay for all employees? Syndio is a Series C technology company leveraging advanced technology and responsible AI to accelerate decision-making, streamline compliance, and democratize insights for consistent, equitable compensation practices at scale. Backed by $83M in investments from Bessemer Venture Partners, Voyager Capital, and Emerson Collective, we are expanding our team and products to help companies align their rewards strategies with their business goals. Our customers are our greatest asset. Syndio partners with many of the world's most recognized and respected enterprises, helping them implement leading-edge compensation solutions with expert guidance. We analyze pay for over 10 million employees across dozens of countries, ensuring fair, defensible rewards that drive better business outcomes. Join us in our mission to help companies make smarter pay decisions they can trust! About the role: We are seeking a talented Staff-level AI Developer to join our applied AI team. In this role, you will be responsible for designing, building, and scaling our AI systems that solve complex problems related to compensation and compliance. You'll work closely in a cross-functional squad that includes data scientists, software engineers, product managers, and business stakeholders. You will have the opportunity to work at the forefront of AI innovation–exploring emerging tools and techniques while translating them into production-ready solutions that deliver real business impact. Why this job is exciting: • Design, develop, and deploy production AI/ML systems that deliver business impact to our customers., • Build and maintain LLM-based applications leveraging context engineering techniques and toolsets., • Collaborate with data scientists to transition approved proof of concepts from a research environment into production., • Integrate AI capabilities into existing products and services through APIs and microservices., • Design and implement evaluation frameworks to assess model accuracy, reliability, and task-specific performance., • Monitor production performance and implement optimizations based on evaluation metrics and real-world usage patterns., • Proficiency developing clean modular and efficient code with Python, • Track record building and deploying AI systems within Google Cloud Platform, familiarity with BigQuery, Firebase, and Vertex AI, • Working knowledge of Google Gemini, OpenAI, and Anthropic APIs, • Familiarity with evaluation methodologies for assessing LLM accuracy, hallucinations, and task-specific performance, • Exposure to—or strong interest in—vector databases, semantic search, agent frameworks, and protocols like MCP for connecting AI systems to external tools and data sources, • Fluent with AI-assisted development tools (Cursor, Claude Code, GitHub CoPilot), • Foundational knowledge of machine learning concepts, model architectures, and LLM capabilities and constraints, • Natural curiosity and passion for staying current with rapidly evolving AI technologies, • Ability to balance innovation with practical business requirements, • Adaptable when navigating ambiguity and rapidly shifting priorities We believe in starting simple, soon — progress over perfection. We value architectural clarity and execution speed. You'll be joining a small, ambitious team committed to high trust, low ego collaboration. It's a dynamic environment where teams embrace ambiguity, adapt quickly to change, and move fast to seize opportunity. As such, we empower engineers to make bold moves and back it up with a culture that supports learning through iteration. Why you'll love it here: • 💰 Competitive Compensation. For this role our base salary is targeted at $205-244k CAD. Final offer amounts are determined by factors such as experience and expertise. We take a geo neutral approach to compensation within the US, meaning that we pay based on job function and level, not location., • 🏆 Syndio Equity. So you can share in Syndio's success., • 🏝 Flexible Vacation Policy. We encourage our team to recharge when they need to, plus paid sick & safe time, compassion leave, parental leave, and voting leave., • 🩺 Medical, Dental, Vision. Syndio pays 90% of employee premiums, and 50% for dependents., • 🏥 Life Insurance & Disability. Syndio covers the full premium., • 🏦 401(k). To help you save for your future Below you'll find an outline of the interview plan for our Staff AI Developer position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision. • 30 min - Phone call with a member of our Talent Team, • 75 min - Zoom interview with the Hiring Manager, • Skills Evaluation - Take-home Assignment, • 75 hr - Technical Interview with Team Syndio is an Equal Opportunity Employer. We are building an inclusive and collaborative workplace as we grow, and we welcome team members regardless of gender/identity, sexual orientation, race or cultural background, religion, physical disability and age.

Job Description VP, Head of Responsible AI Our client is seeking a visionary VP, Head of Responsible AI to architect trust across our enterprise AI initiatives. Reporting jointly to the CIO and General Counsel, you will accelerate AI adoption while embedding ethical, legal, and security guardrails in a data-centric operations environment. In a data-centric operations environment, this role serves as the bridge between technical innovation and legal safeguard — enforcing a dual mandate: accelerating AI adoption while minimizing systemic risk. Responsibilities: • Define and operationalize a 3-year Responsible & Secure AI maturity roadmap aligned with client commitments and global regulations., • Co-lead the AI Governance Committee with CIO/GC to unify AI approval and deployment decisions., • Serve as enterprise spokesperson on AI Trust for clients, regulators, and industry forums., • Establish the "Source of Truth" for all AI assets (model registries, lineage, audit trails)., • Oversee red-teaming, stress testing against prompt injection, model extraction, and data poisoning., • Embed security into LLMOps/DevSecOps pipelines for "Secure by Design" agentic systems., • Ensure RAG/fine-tuning workflows prevent PII leakage and client data cross-contamination., • Implement protocols to discover and govern shadow AI across business units., • Drive 100% compliance with EU AI Act, NIST AI RMF, ISO 42001, and US state laws (e.g., Colorado AI Act)., • Mandate bias detection/mitigation and algorithmic fairness protocols., • Enforce Human-in-the-Loop (HITL) requirements for high-stakes AI operations., • Support client negotiations with transparency on AI data protection., • Partner with Business Units to RAI-enable workflows without bypassing risk guardrails., • Vet foundation model providers (OpenAI, Anthropic) and open-source libraries., • Ensure AI systems align with EXL's cloud, data governance, and platform strategies., • Oversee policy adherence via audits, dashboards, and compliance reviews., • Lead enterprise training and culture-building for responsible AI., • Build/mentor a team of AI governance leads, ethicists, and security experts. Qualifications: Required: • 15 years in technical, legal, or risk leadership; 5 years dedicated to AI/ML governance, security, or ethics., • Hybrid expertise: Discuss Transformer architectures/vector DBs with engineers AND liability/indemnification with Legal., • Deep fluency in NIST AI RMF, ISO 42001, EU AI Act., • Proven experience building "Governance-as-a-Service" in global, regulated, client-facing enterprises., • Direct experience with LLMOps, RAG security, red-teaming, shadow AI mitigation., • Track record leading AI governance committees or maturity programs., • Comfortable in client-facing roles providing AI trust assurances.

Job DescriptionAbout zaimler AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it. zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve. zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're growing and deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of enterprise AI runs on, we'd love to talk. About the Job We’re looking for a Forward-Deployed Engineer to join our founding team and bring our AI-native data infrastructure to life in real-world environments. This is a hybrid role blending infrastructure, product, and delivery—you’ll work across systems, tools, and teams to bring new deployments from concept to scale. Think of it as a "jack-of-all-systems" role: one foot in Kubernetes and Ray clusters, the other in semantic pipelines and user-facing use cases. You’ll be a first responder, architect, and operator—deploying zaimler’s semantic infrastructure into dynamic enterprise settings, collaborating closely with ML and infra engineers, and making sure customers get value from day one. This role prefers candidates in or aligned to the Eastern Time Zone (EST) & will require travel onsite to customer locations. What You Will Be Doing • Build, deploy, and scale zaimler’s platform in diverse customer environments (Kubernetes-native, often hybrid cloud), • Own the infrastructure stack: provisioning, scaling, monitoring, and incident handling for data/ML pipelines., • Stand up and optimize distributed compute systems using Ray, Kubernetes, and supporting cloud services., • Bridge ML and infra—help ML engineers productionize knowledge extraction, entity linking, and retrieval pipelines, • Write Terraform, Helm charts, Dockerfiles, and bash scripts that others rely on, • Contribute to internal tooling, automation, and observability to make zaimler repeatable and scalable., • Interface directly with early customers to understand their environment, workflows, and edge cases.Prior Experience, • 3+ years of experience in backend or infrastructure roles (infra/platform, SRE, or devops welcome), • Deep familiarity with Kubernetes, Docker, Terraform, and Helm, • Experience managing or deploying distributed compute frameworks (Ray, Dask, Spark, etc.), • Fluency in at least one scripting language (Python, Bash, Go preferred), • Strong debugging skills across the stack—from network hiccups to memory leaks, • Experience deploying in cloud-native environments (AWS/GCP/Azure), • Comfortable being customer-facing and managing ambiguity in real-time, • Strong sense of ownership and bias toward action in early-stage environmentsNice to Haves, • Experience deploying or integrating LLMs or vector databases, • Background in ML Ops or building/operating data infrastructure at scale, • Familiarity with GPU optimization, multi-tenancy, or air-gapped environments, • Prior startup or zero-to-one deployment experience, • Familiar with Ray Serve, VLLM, or similar frameworks

Location: US - Remote Experience: 8+ years in Cloud/Platform Engineering or Infrastructure, with a proven track record of leading cross-functional initiatives and influencing organizational AI strategy. We are looking for a visionary Staff AI-Native Platform Engineer to lead the evolution of our technical foundation. In this high-impact role, you will move beyond traditional automation to architect an AI-native ecosystem that integrates Generative AI into every layer of our Development Platform. As a technical leader within the Platform organization, you won’t just be maintaining infrastructure, you will be reimagining the developer experience (DevEx). You will be the primary advocate for GenAI, fostering a culture of “AI-first” engineering by building agentic workflows that accelerate Cloud Orchestration, CI/CD, Observability, and FinOps. We need a creative engineer who can bridge the gap between cutting-edge LLM capabilities and robust, production-grade platform tooling. * AI-First Development Platform: Design and build unified interfaces where AI agents manage complex tasks like environment provisioning, automated PR reviews, and self-documenting codebases. * Intelligent Orchestration: Embed AI-driven intelligence into CI/CD pipelines and Observability stacks to enable predictive scaling, automated incident triage, and self-healing systems. * Autonomous FinOps: Evolve AI-assisted FinOps workflows to automate cost attribution, anomaly detection, and optimization recommendations across AWS and other cloud environments. * Governance & Guardrails: Implement AI-driven governance to ensure architectural standards and security policies are met without slowing down developer velocity. * Agentic Tooling: Develop production-grade internal tools that use agentic reasoning to solve "day two" operational challenges for product teams. * Internal Developer Portal (IDP): Integrate natural language interfaces into our IDP, allowing developers to interact with the platform through conversational AI. * Actionable Insights: Transform raw telemetry into “executive-ready” insights using advanced data modeling and AI-driven visualization. * Strategic Advisory: Partner with senior leadership to model the technical and operational trade-offs of various AI architectural decisions (e.g., Build vs. Buy, Model Selection). * Team Upskilling: Act as a force multiplier by mentoring engineers on advanced AI tooling, prompt engineering for infrastructure, and the deployment of agentic systems. * Community Building: Stay at the forefront of the GenAI landscape, regularly sharing insights and driving the adoption of emerging tools and patterns across the organization. * Platform Expertise: 8+ years of experience in Cloud Engineering (AWS preferred), with deep knowledge of Kubernetes, Terraform/CloudFormation, and modern CI/CD patterns. * AI/ML Applied Logic: Expert-level experience applying AI techniques (summarization, RAG, agentic reasoning) to real-world operational workflows. You understand how to make LLMs "useful" in a production environment. * Advanced Programming: Expert Python skills and experience with AWS SDKs. You are comfortable building complex integrations and custom CLI/API tools. * The "Staff" Mindset: A history of leading large-scale, cross-functional projects. You can navigate ambiguity, build consensus across teams, and deliver measurable business impact. * Creative Evangelism: The ability to present complex AI concepts to both technical and non-technical stakeholders, inspiring teams to shift toward AI-native workflows. * Product Thinking: Experience building Internal Developer Portals (IDP) with a focus on "Platform as a Product" and user-centric design. * Experience with LangChain, LlamaIndex, or other AI orchestration frameworks. * Contributions to open-source platforms or AI projects. * Experience with vector databases and fine-tuning models for domain-specific tasks. The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. Remote USA $152,100 - $190,100 USD OUR OPPORTUNITY Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management. WHAT WE OFFER Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program! For more information, visit ___. Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide. All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability or any other legally protected status. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws. If you are based in California, we encourage you to read this important information for California residents. Link: ___ Please be advised that Natera will reach out to candidates with a @___ email domain ONLY. Email communications from all other domain names are not from Natera or its employees and are fraudulent. Natera does not request interviews via text messages and does not ask for personal information until a candidate has engaged with the company and has spoken to a recruiter and the hiring team. Natera takes cyber crimes seriously, and will collaborate with law enforcement authorities to prosecute any related cyber crimes. For more information:

Job Description: Overview: We don't simply hire employees. We invest in them. When you work at Chatham, we empower you - offering professional development opportunities to help you grow in your career, no matter if you've been here for five months or 15 years. Chatham has worked hard to create a distinct work environment that values people, teamwork, integrity, and client service. You will have immediate opportunities to partner with talented subject matter experts, work on complex projects, and contribute to the value Chatham delivers every day. Chatham Financial is looking for an AI Solutions Engineer to design, build, and deploy custom AI solutions that address high-value business workflows. This is a hybrid technologist and trusted advisor role.You'llwork closely with stakeholders to understand operational challenges and build AI-powered solutions that create measurable value.You'llown problems end-to-end-from discovery through production. This is a hybrid technologist and trusted advisor role.You'llembedwith client teams, understand their operational challenges, and build AI-powered solutions that create measurable value. Think startup CTO meets management consultant-you'llownproblems end-to-end. What You'll Do: Client Engagement * Work directly with private equity firms, real estate investors, and capital markets clients to understand their workflows andidentifyAI opportunities * Lead discovery conversations to uncover pain points and scope solutions * Present recommendations to both technical and executive stakeholders Solution Design & Architecture * Architect custom AI solutions including workflow automation, data extraction, intelligent reporting, and AI agents * Evaluate when to use LLMs vs. traditional ML vs. rule-based approaches * Design systems that integrate with existing client infrastructure Hands-On Building * Write production code-Python, modern web frameworks, LLM integrations (OpenAI, Anthropic, etc.) * Build RAG systems, agentic workflows, and custom AI applications * Own the full stack from data ingestion to user interface Rapid Prototyping * Build working prototypes in days/weeks, not months * Validate value quickly with real users and real data * Iterate based on feedback and measured outcomes Production Deployment * Take solutions from prototype to production * Ensure reliability, security, and maintainability * Support ongoing optimization and enhancement Contributors to your success: * 7+ years of software engineering experience, ideally with client-facing or consulting exposure * Strong programming skills in Python; experience with TypeScript/JavaScript a plus * Hands-on experience building with LLMs (GPT, Claude, etc.)-RAG, prompt engineering, fine-tuning, or agentic systems * Experience taking AI/ML projects from prototype to production * Excellent communication skills-can explain technical concepts to executives and collaborate with non-technical stakeholders * Comfortable with ambiguity-can scope problems, make decisions, and own outcomes end-to-end * Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent experience * Experience in financial services, private equity, or real estate * Background at a startup (especially as early engineer) or consulting firm * Experience with data pipelines, ETL, and working with messy enterprise data * Familiarity with cloud platforms (AWS, Azure, GCP) * Experience with vector databases, embeddings, and semantic search For New York based candidates, the compensation range for the position is expected to be between $200,000 and $275,000 annually. Total compensation, including base pay, discretionary individual bonus and company bonus, may be higher than range listed, depending on applicant's skills, qualifications, and experience. Benefits include health insurance, life and disability insurance, 401k, EAP, paid holidays and paid time off. About Chatham Financial: Chatham Financial is the leading independent capital markets advisor, delivering an integrated blend of expert advice and powerful technology to help you reduce risk and seize opportunity. With decades of capital markets strategy, execution, monitoring, and performance expertise, we serve as an unwavering advocate for your best interests and your innovation partner. Our technology platform unifies data across assets, debt, and derivatives, giving you unmatched agility, transparency, and insight. It's clear ahead. Our commitment is to carry that light forward in every partnership, every solution, and every market we serve. We help guide the way-giving clients the insight and momentum to move forward with confidence, no matter what lies ahead.

Job Description: Architect and own the AI context platform Design end-to-end platform architecture: ingestion ? parsing/chunking ? enrichment ? embeddings ? vector indexing ? retrieval/serving Define scalable patterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage a

Job Description: Build and contribute to the AI context platform Implement end-to-end pipelines: ingestion → parsing/chunking → enrichment → embeddings → vector indexing → retrieval/serving Build and maintain patterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources Contribute to retrieval quality improvements (query strategies, hybrid search, metadata filtering) in partnership with AI engineers Deliver semantic and governed data products Requirements: 3–6 years in data engineering or data platform roles with strong hands-on delivery Strong SQL and Python (or Scala/Java); solid production engineering habits Experience designing and operating cloud data pipelines at scale Experience working with unstructured data processing and search/retrieval concepts Clear communicator who can work effectively across technical and functional teams Benefits: Medical, dental and vision coverage 401(k) plan with a generous employer match Employee stock purchase plan Generous Paid Time Off policy Paid parental leave and adoption assistance Wellness Program with free annual health screenings and coaching

Job Description: Perform signal integrity (SI) simulations using tools such as HyperLynx, HFSS, or CST Identify and resolve issues related to crosstalk, signal loss, reflections, and other performance degradations in high-speed designs. Analyze PCB layout designs to ensure optimal signal performance, providing feedback and recommendations to layout and hardware design teams. Collaborate with hardware engineers to optimize high-speed signal paths, ensuring adherence to specifications for interfaces like DDR5, PCIe, USB4, SerDes, and Ethernet. Evaluate and validate signal integrity for power delivery networks (PDN) to minimize noise, ground bounce, and power/ground integrity issues. Work closely with PCB layout, hardware, and mechanical teams to ensure design choices align with signal integrity best practices. Develop and implement test strategies for verifying signal integrity on prototypes and final products using tools like oscilloscopes, vector network analyzers (VNA), and time domain reflectometry (TDR). Create and maintain signal integrity design guidelines, best practices, and checklists to support hardware engineers throughout the product development lifecycle. Diagnose and resolve SI issues during the bring-up phase of new products, ensuring minimal impact on time-to-market. Requirements: Bachelors or Masters degree in Electrical Engineering, Electronics Engineering, or a related field. 5+ years of experience in signal integrity and related areas in hardware engineering with hands on experience on LPDDR5, PCIe, USB4, SerDes, and Ethernet protocols. Strong understanding of high-speed signal transmission principles, including impedance, crosstalk, noise, and signal attenuation. Proficiency in SI analysis tools such as Ansys HFSS, SIWave, CST or similar industry-standard software. Hands-on experience with lab equipment such as oscilloscopes, VNAs, TDRs, and protocol analyzers. Ability to contribute to process improvements and the development of new methodologies for signal integrity analysis. Benefits: Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

A leading data platform company is seeking a Senior Backend Software Engineer to play a crucial role in building scalable AI-native data infrastructure.This position emphasizes backend service design, utilizing C/C++ to optimize performance across distributed systems.The ideal candidate will bring o

A leading data platform company is seeking a Senior Backend Software Engineer to develop scalable AI-native data infrastructure. The role involves architecting distributed vector databases using C/C++. Candidates should have over 5 years of experience in backend engineering and strong proficiency in

Job Description Vector Marketing, who has been around for over 40 years, is currently interviewing now for part time sales positions. Basic responsibilities include working with customers through appointments, selling our products, setting up appointments, and placing orders. Great starting pay, not based on sales or results. Apply online to check for an opening near you, interview within the week. Position Details: • Paid Weekly – base or commission, whichever is higher for the week. We have a commission structure set up based on performance. Reps are paid 30.00 base-appt (per presentation, not based on sales or results). There is an opportunity to make more, but there is still a fallback for the sales rep to make an income even if they have an off week., • Solid training – We’ve been training people to do well for over 40 years. Even if someone doesn’t decide to stay with us long term, the sales, networking, & communication skills they build are needed for any field., • Advancement – Reps who work here long term (even if they work part time) have an opportunity to move along several different paths including management and career sales professional., • Location – Sales reps work locally after training. Meetings and training are held in the office., • Flexible scheduling – We help our reps create a schedule that works best for them. Some work as much as possible, some work part time, and others choose to earn extra income around other commitments such as internships, classes, vacations, full time jobs, or family obligations. We have a summer work program for people looking for seasonal work., • Product - We work with Cutco products that are used in the home focusing on the kitchen and some gardening tools as well. Previous experience & knowledge about home goods or sales isn’t needed. Basic Requirements: • Enjoy working with people, • All ages eighteen plus or seventeen and a 2026 high school graduate, • Conditions apply, • Willing to learn and apply new skills Who would do well: People who have done well with us in the past have had experience in admin, retail, fast food, cashier, administrative assistant, receptionist, office work, server, landscaping, and in just about any field you can imagine. Some none at all! We welcome all applicants who have a positive attitude and enjoy working with people. This entry level sales position is a great fit for people who are looking to work around their schedule. If you are a student looking for summer work or just someone who is looking for a flexible schedule, our opportunities can work around your needs. If you think you would be a great fit for our sales team, fill out the contact information and a receptionist will send you a text about setting up a virtual interview with a manager. We encourage applicants of all ages and experience, as we do not discriminate on the basis of an applicant’s age.