Trabajos databricks en Bayonne, New Jersey - Page 3Crear alertas

Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role Join Hinge as a Senior Machine Learning Engineer, where you'll lead the application of AI and machine learning to effectively mitigate the impact of bad actors, remove policy violating content, and ensure user safety on the platform. Working closely with an expanding Trust & Safety team, you will collaborate with product managers, data scientists, engineers, and analysts to develop impactful AI/ML solutions. In this high-impact position within a small, dynamic team, you'll have the opportunity to play a foundational role in shaping how Hinge utilizes AI and machine learning in various contexts. Your expertise will be instrumental in creating a safer and more meaningful user experience on their journey to find an intimate connection.Responsibilities • Develop, deploy, and maintain end-to-end machine learning models to identify and mitigate bad actors, remove policy-violating content, and ensure user safety., • Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines., • Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions., • Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations., • Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety., • Stay abreast of new trends and research in AI/ML that can be applied to Trust & Safety initiatives to improve detection, user safety, and stay ahead of potential threats.What We're Looking For, • Strong programming skills: Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines, • Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus ., • System design & architecture: Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference., • Evaluation frameworks for LLMs: Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features., • Cloud and data platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow is a plus., • Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow., • Strategic technical leadership skills: Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives., • Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds., • Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation.Prior Experience, • 4+ years of experience, depending on education, as an MLE or data scientist. Previous experience working in Trust & Safety or related fields (e.g., fraud detection, content moderation, compliance) is preferred., • 2+ years of experience in applying end-to-end machine learning models, including data collection, model training, deployment, and monitoring in an industry setting, • 1+ years of experience integrating LLMs in real-world applications with the appropriate baseline metrics and evaluation methodologies., • 1+ years of experience utilizing ML infrastructure components such as a feature store, model training environment, model serving environment, observability, workflow orchestrator, etc. #Hinge .

Job Description StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we're here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world. We're rebuilding our data foundation from the ground up - and we're looking for a Senior Analytics Engineer who thrives at the intersection of data infrastructure, business context, and cross-functional collaboration. If you're excited by the idea of owning foundational systems that will power pricing, personalization, experimentation, and more—this role is for you. Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA About the Team: As a Senior Analytics Engineer at StubHub, you'll be a force multiplier for the entire company. You'll build scalable data products and frameworks that empower analysts, data scientists, and business leaders to make better, faster decisions. You'll bring order to chaos, anticipate data needs before they arise, and partner with stakeholders across engineering, product, and business teams to help us unlock the full value of our data. What You'll Do: • Own the development of cross-functional data models, core business metrics, and self-service dashboards/tools., • Build, document, and maintain robust data pipelines using tools like dbt, Airflow, Snowflake, BigQuery, or Databricks., • Anticipate and solve common data access patterns across product, marketing, finance, and operations teams., • Partner closely with data scientists, analysts, and software engineers—often serving as the bridge between product needs and data infrastructure., • Define and scale analytical frameworks that support experimentation, decision-making, and business health monitoring., • Act as a domain expert in one or more business areas (e.g., pricing, supply, demand, user growth), becoming a go-to thought partner for leadership., • 5 - 10 years of experience in analytics engineering, data engineering, or business intelligence in a fast-paced, high-growth environment., • Expert SQL skills and strong proficiency in Python (or another programming language like Java)., • Hands-on experience building data pipelines and models with tools like dbt, Airflow, and Snowflake (or equivalent)., • Experience with BI tools such as Looker, Tableau, or Mode, and a strong understanding of enabling self-serve analytics., • Familiarity with both batch and streaming data processing patterns., • An ability to translate messy, real-world business problems into elegant, scalable data systems., • A collaborative mindset with a passion for partnering with non-technical stakeholders to unlock insights and drive impact., • Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale., • Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact., • Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed., • Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options. The anticipated gross base pay range is below for this role. Actual compensation will vary depending on factors such as a candidate's qualifications, skills, experience, and competencies. Base annual salary is one component of StubHub's total compensation and competitive benefits package, which includes equity, 401(k), paid time off, paid parental leave, and comprehensive health benefits. Salary Range$175,000—$250,000 USDAbout UsStubHub is the world's leading marketplace to buy and sell tickets to any live event, anywhere. Through StubHub in North America and viagogo, our international platform, we service customers in 195 countries in 33 languages and 49 available currencies. With more than 300 million tickets available annually on our platform to events around the world -- from sports to music, comedy to dance, festivals to theater -- StubHub offers the safest, most convenient way to buy or sell tickets to the most memorable live experiences. Come join our team for a front-row seat to the action. For California Residents: California Job Applicant Privacy Notice found hereWe are an equal opportunity employer and value diversity on our team. We do not discriminate on the basis of race, color, religion, sex, national origin, gender, sexual orientation, age, disability, veteran status, or any other legally protected status.

Job Description Our client RibbitZ is looking for Senior Software Engineer-LLM Evaluation to work remotely. As a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections in Python, JavaScript (including ReactJS), C/C++, Java, Rust, and Go; evaluating and refining AI-generated code for efficiency, scalability, and reliability; and working with cross-functional teams to enhance enterprise-level AI-driven coding solutions. What Does a Typical Day Look Like? • Working on AI model training initiatives by curating code examples, building solutions, and correcting code in Python, JavaScript (including ReactJS), C/C++, Java, Rust, and Go., • Evaluate and refine AI-generated code to ensure that it is efficient, scalable, and reliable., • Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks., • Build agents that can verify the quality of the code and identify error patterns., • Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them, • Several years of software engineering experience (+5 years), including, 2+years of continuous full-time experience at a top-tier product company (e.g., Google, Stripe, Amazon, Apple, Meta, Netflix, Microsoft, Datadog, Dropbox, Shopify, PayPal, IBM Research)., • Strong expertise in building full-stack applications and deploying scalable, production-grade software using modern languages and tools., • Deep understanding of software architecture, design, development, debugging, and code quality/review assessment., • Software Engineering profiles only, • Candidates must be based in the US, • 5+ years of relevant experience, • Google (Alphabet), • Apple, • Amazon, • Meta (Facebook), • Netflix, • Microsoft, • Tesla, • NVIDIA, • Adobe, • Salesforce, • Github, • Atlassian, • hashiCorp, • Databricks, • Snowflake, • Cloudflare, DigitalOcean, MongoDB, • Elastic, Confluent, Airbnb, Dropbox, • Stripe, Palantir, Uber, Lyft, • Square (Block), Twilio, Snap Inc., • Pinterest, Figma, Oracle, Cisco, • Paypal, Doordash, Rivian, Reddit, Coinbase, Splunk, • Spotify, Goldman Sachs, Morgan Stanley, • JP Morgan Chase, Capital One, • Plaid, Shopify, Intuit, Workday, ServiceNow, • Hugging Face, VMware, Brex, Wise, • Epic Games, Unity Technologies, • Activision Blizzard, Riot Games, Valve, • Huawei, Bloomberg, ByteDance, • Alibaba, Baidu, Notion, Klarna, • Instacart, Zillow.

Job DescriptionAbout Us Madison Energy Infrastructure is one of the largest, and fastest-growing, commercial and industrial solar asset owners in the country. We manage hundreds of distributed generation sites across the U.S., with production data flowing in hourly and financial outcomes tied directly to the accuracy of our reporting. We believe great asset management starts with great data. Not dashboards for dashboards' sake — but accurate, timely, decision-ready information that operations, finance, and leadership can trust. We're scaling fast. That means complexity, volume, and real responsibility. We need people who can keep up — and raise the bar while they're at it. About You You are disciplined, data-oriented, and dependable. You know the Excel shortcuts, you build pivot tables in your sleep, and you are curious enough to see whether Claude can generate a report faster than you can and disciplined enough to validate every number it produces. You take full ownership of your work. You are fluent in SQL, with working knowledge of Python and or R, and you are comfortable using code when it is the right tool for the job. You understand the expectations of a corporate environment where accuracy, responsiveness, and follow through matter and you perform well under that pressure. You are comfortable operating in Snowflake, PowerBI, Salesforce, and Excel, and you know where logic belongs. You manage multiple requests, communicate priorities clearly, and close the loop. You want to be in a growth environment. You want responsibility, high standards, and the opportunity to earn trust by delivering consistently. And yes you probably enjoy the quiet satisfaction of a clean model, a reconciled dataset, and a report that holds up when it really counts. The Role As a Senior Data Analyst, Asset Management, you will be responsible for the daily-critical reporting and analytical backbone of our asset management operation. This is not a passive reporting role. You will own production analysis, financial views, and data automation workflows that the business relies on every day. If something breaks, you'll find it. If something doesn't make sense, you'll dig in. If a better system is needed, you'll help build it. You'll work closely with Asset Management, Finance, and our Senior Manager of Data Analytics to ensure that what we see, what we bill, and what we report is correct. Key Responsibilities • Own daily, weekly, and monthly production reporting across a large and growing solar portfolio (AlsoEnergy → Snowflake → PowerBI), • Ensure production, financial, and site-level data is accurate, reconciled, and dependable, • Turn around one-off reporting requests quickly and accurately, understanding the context behind the data, • Maintain and tweak the PowerBI dashboards that answer real business questions, • Use Snowflake as the system of calculation and truth, not Excel hacks, • Manage and maintain data automation workflows, including:, • Microsoft PowerApps / Power Automate flows, • Salesforce syncs and reporting layers, • Identify data integrity issues proactively (communications loss, missing data, inconsistencies), • Support Asset Management and Finance with clean, reliable analysis for decision-making, • Communicate clearly about priorities, timelines, and tradeoffs when multiple requests are in flight, • Continuously improve reporting systems so recurring questions become self-serviceWhat You Bring, • 4+ years in a finance, accounting, or data analysis role, • 3+ year exposure to solar or energy data (nice to have, not required), • 2+ years hands-on experience with Salesforce (reporting, dashboards, data structure), • 2+ years working directly in Snowflake/DataBricks, • 10+ years of Excel experience, • 2+ years building reports and models in PowerBI, • 1+ year working with Microsoft PowerApps / Power Automate, • Strong skills in SQL, Python, and/or R, • Background in statistics and analytical thinking, • Obsessive attention to detail — your outputs don't need rework, • Ability to manage complex workflows and multiple priorities without dropping balls, • Comfortable in a fast-moving, scaling environment, • Proactive, helpful, and willing to dig in, • Strong desire to learn and get better, • Professional experience with Zoom, Slack, Outlook, Teams, Adobe, etc., • PTO and company holidays, • Medical, dental, vision, • Employer-paid short-term disability, long-term disability, life insurance, • 401(k) and company match, • Professional development stipend, • Strong culture of collaboration, performance, and personal growth$90,000 - $120,000 a yearThe actual salary offered may vary depending on job-related factors including, but not limited to knowledge, skills, experience and location.How We WorkAt Madison Energy Infrastructure, we believe in the power of clean energy infrastructure to drive real impact—for our customers, our partners, and the communities we serve. We've quickly emerged as a preeminent developer, investor, and operator of distributed generation, helping organizations across sectors meet their energy goals with certainty, speed, and trust. Our robust portfolio consists of over half a gigawatt of clean energy infrastructure projects across more than 25 states.We're building a team that thrives on ownership and ambition. As we expand into direct, end-to-end services for Fortune 500 companies, public entities, and nonprofits alike, we rely on collaborative thinkers who bring structure to complexity, energy to execution, and curiosity to every challenge.Our environment is fast-paced and outcome-oriented—but grounded in the belief that how we work together matters as much as what we deliver. If you're excited to shape the future of clean energy and be part of a high-performance, high-integrity team, we'd love to meet you.Madison Energy Infrastructure is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.