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Job DescriptionAbout Quizlet: At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. Our $1B+ learning platform serves tens of millions of students every month, including two-thirds of U.S. high schoolers and half of U.S. college students, powering over 2 billion learning interactions monthly. We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s Build the Future of LearningJoin us to design and deliver AI-powered learning tools that scale across the world and unlock human potential. About the Team (Applied AI): Our mission is to invent and deploy the next generation of intelligent, personalized, and adaptive learning experiences. We’re consolidating AI efforts across the company into a unified portfolio and are accountable for a disproportionate share of Quizlet’s growth and product differentiation. You’ll partner closely with Product, Data Science, and the AI & Data Platform to deliver an AI‑driven learning coach that’s recognized as best‑in‑class. About the Role: As Sr. Staff Applied AI Engineer, you will be the hands‑on technical leader shaping Quizlet’s AI develop in one of the two complementary domains: • Personalization & Ranking – retrieval and ranking systems that match learners with the right content, experiences, and monetization moments across surfaces (search, feed, notifications, ads). • Own the technical roadmap for applied AI spanning personalization, ranking, search, recommendations, and GenAI/LLM systems; tie modeling work directly to business metrics (engaged learners, conversion, retention, revenue), • Design end‑to‑end ML systems: candidate sourcing, embedding platforms & ANN retrieval, multi‑stage ranking (early/late), and value modeling with guardrails for fairness and integrity, • Lead LLM‑based features: stand up RAG pipelines, instruction‑/preference‑tuning (e.g., SFT/DPO/RL‑style), prompt engineering, and latency/cost‑aware inference strategies; define offline evals + human‑in‑the‑loop and online success metrics, • Create a “Learner 360” representation by synthesizing behavior signals, explicit inputs, and conversational context into robust embeddings reused across surfaces, • Institutionalize evaluation: build an eval harness for both ranking and generative systems (offline metrics like NDCG/AUC/BLEU/BERTScore; quality/safety scorecards; inter‑rater reliability), and close the loop with online A/B experiments, • Ship reliably at scale: drive training‑serving consistency, drift detection, canarying, rollbacks, on‑call standards for model services, and strong CI/CD for features & models, • Mentor and uplevel a high‑performing group of ML/SWE peers; set crisp technical direction and raise the bar on code quality, experimentation rigor, and reproducibility, • Partner deeply with Product, Design, Legal, and Data Science on objectives, risk/benefit tradeoffs, and responsible AI practices, • Stay current with the state of the art (RecSys, LLMs, multimodal) and selectively introduce methods that measurably improve learner outcomesWhat you bring to the table:, • 10+ years of industry experience in applied ML/AI or ML‑heavy software engineering, including staff‑level impact leading cross‑functional efforts end‑to‑end, • BS/MS/PhD in CS, ML, or related quantitative field (or equivalent experience), • Proven record shipping large‑scale ranking/personalization or search systems (retrieval, Two‑Tower/dual encoders, multi‑task rankers), and improving online metrics (e.g., CTR, session depth, retention), • Hands‑on with LLM/GenAI systems: data curation, fine‑tuning (SFT/PEFT, preference optimization), prompt engineering, evaluation, and productionization (latency/cost/safety), • Deep fluency in Python/PyTorch, data and feature engineering, distributed training/inference on GPUs, and modern MLOps (model registry, feature stores, monitoring, drift), • Strong experiment design (offline/online), metrics literacy, and skills translating ambiguous product goals into tractable modeling roadmaps, • Demonstrated technical leadership: mentoring senior engineers, setting architecture, and driving consensus amid ambiguityBonus points if you have:, • EdTech or consumer mobile experience; conversational tutoring or learning science‑informed modeling, • Publications/open‑source with RecSys/LLMs (e.g., RecSys, KDD, NeurIPS, ICLR, ACL), or contributions to safety/guardrails tooling, • Experience building on a modern MLOps stack (feature mgmt, orchestration, streaming, online inference at scale)Compensation, Benefits & Perks:, • Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a starting base salary of $282,000 - $344,000, depending on location and experience, as well as company stock options, • Collaborate with your manager and team to create a healthy work-life balance, • 20 vacation days that we expect you to take!, • Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice), • Employer-sponsored 401k plan with company match, • Access to LinkedIn Learning and other resources to support professional growth, • Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits We strive to make everyone feel comfortable and welcome!We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership. We provide a transparent setting that gives a comprehensive view of who we are! In Closing: At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high-quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together.” Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion. As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us! To All Recruiters and Placement Agencies: At this time, Quizlet does not accept unsolicited agency resumes and/or profiles. Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionAbout Quizlet: At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. Our $1B+ learning platform serves tens of millions of students every month, including two-thirds of U.S. high schoolers and half of U.S. college students, powering over 2 billion learning interactions monthly. We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s Build the Future of LearningJoin us to design and deliver AI-powered learning tools that scale across the world and unlock human potential. About the Team (Applied AI): Our mission is to invent and deploy the next generation of intelligent, personalized, and adaptive learning experiences. We’re consolidating AI efforts across the company into a unified portfolio and are accountable for a disproportionate share of Quizlet’s growth and product differentiation. You’ll partner closely with Product, Data Science, and the AI & Data Platform to deliver an AI‑driven learning coach that’s recognized as best‑in‑class. About the Role: As an Applied AI Engineer, you will be working at the forefront of our AI strategy, shaping Quizlet’s AI develop in one of the two complementary domains: Personalization & Ranking – retrieval and ranking systems that match learners with the right content, experiences, and monetization moments across surfaces (search, feed, notifications, ads). Generative AI & Agentic Systems – LLM‑powered tutoring, content understanding/synthesis, and tools that boost learner outcomes and creator productivity. You will work on a variety of models and modeling systems (from Two‑Tower retrieval and multi‑task rankers to RAG/LLM pipelines), ensure robust evaluation and responsible deployment We’re happy to share that this is an onsite position in our San Francisco office. To help foster team collaboration, we require that employees be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company. We believe that this working environment facilitates increased work efficiency, team partnership, and supports growth as an employee and organization.In this role, you will: • Contribute to the technical roadmap for applied AI across personalization, ranking, search, recommendations, and GenAI/LLM systems; help connect modeling work to business metrics (engaged learners, conversion, retention, revenue), • Build components of end‑to‑end ML systems: candidate sourcing, embedding platforms & ANN retrieval, multi‑stage ranking (early/late), and value modeling with guardrails for fairness and integrity, • Implement LLM‑based features: build RAG pipelines, apply instruction‑/preference‑tuning techniques (e.g., SFT/DPO), optimize prompts, and improve latency/cost‑aware inference; contribute to offline evals + human‑in‑the‑loop and online success metrics, • Help develop "Learner 360" representations by working with behavior signals, explicit inputs, and conversational context to create robust embeddings reused across surfaces, • Support evaluation infrastructure: contribute to the eval harness for both ranking and generative systems (offline metrics like NDCG/AUC/BLEU/BERTScore; quality/safety scorecards), and help close the loop with online A/B experiments, • Ship reliable systems at scale: ensure training‑serving consistency, implement drift detection, follow canarying/rollback protocols, participate in on‑call rotation for model services, and maintain strong CI/CD for features & models, • Collaborate with and learn from senior ML/SWE teammates; write high‑quality code and follow best practices for experimentation rigor and reproducibility, • Work closely with Product, Design, Legal, and Data Science on objectives, tradeoffs, and responsible AI practices, • Stay current with ML research (RecSys, LLMs, multimodal) and propose new methods that could improve learner outcomesWhat you bring to the table:, • 5-8+ years of industry experience in applied ML/AI or ML‑heavy software engineering, • BS/MS in CS, ML, or related quantitative field (or equivalent experience), • Experience building ranking/personalization or search systems (retrieval, Two‑Tower/dual encoders, multi‑task rankers) and contributing to online metric improvements (e.g., CTR, session depth, retention), • Hands‑on experience with LLM/GenAI systems: data curation, fine‑tuning (SFT/PEFT, preference optimization), prompt engineering, evaluation, and productionization considerations (latency/cost/safety), • Strong skills in Python/PyTorch, data and feature engineering, distributed training/inference on GPUs, and familiarity with modern MLOps (model registry, feature stores, monitoring, drift), • Solid experiment design (offline/online), metrics literacy, and ability to translate product goals into modeling solutions, • Strong collaboration skills and eagerness to learn from senior engineers; some experience mentoring junior teammates is a plusBonus points if you have:, • EdTech or consumer mobile experience; conversational tutoring or learning science‑informed modeling, • Publications/open‑source with RecSys/LLMs (e.g., RecSys, KDD, NeurIPS, ICLR, ACL), or contributions to safety/guardrails tooling, • Experience building on a modern MLOps stack (feature mgmt, orchestration, streaming, online inference at scale)Compensation, Benefits & Perks:, • Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a starting base salary of $183,000 - $248,000, depending on location and experience, as well as company stock options, • Collaborate with your manager and team to create a healthy work-life balance, • 20 vacation days that we expect you to take!, • Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice), • Employer-sponsored 401k plan with company match, • Access to LinkedIn Learning and other resources to support professional growth, • Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits We strive to make everyone feel comfortable and welcome!We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership. We provide a transparent setting that gives a comprehensive view of who we are! In Closing: At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high-quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together.” Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion. As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us! To All Recruiters and Placement Agencies: At this time, Quizlet does not accept unsolicited agency resumes and/or profiles. Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet.#LI-FT We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description East Bay Innovations Supported Employment Services (SES) Childcare Specialist (Part-Time) About Our Organization: Established in 1994, East Bay Innovations (EBI) is a nonprofit human services organization that supports people with developmental disabilities, such as intellectual disabilities, autism, and cerebral palsy. Our person-centered services support people to live in their own homes, make choices about how they live, work in jobs of their choosing, and enjoy being part of their communities. We seek to further the human rights and empowerment of people with disabilities, and hire people who care about social justice and want to make a difference in the lives of others. EBI has been named a winner of San Francisco Chronicle’s Top Workplaces Award for 2023, 2024, and 2025! About the position: In our Supported Employment Services (SES) department, the Childcare Specialist provides training and support to individuals with disabilities in community work settings or internship sites, including External Situational Assessments and Personal Vocational Social Adjustments, Tailored Day Services, Job Coaching, Project SEARCH, Tutoring, and Excel Internships. Assists job developer in the support of consumers regarding vocational evaluation, planning, and placement. Provides support during interviews. Assists with Ticket to Work, development of task analysis for new work sites, development of assistive tools, and outreach. Education: • Part-Time, 30 hours per week., • Working in Contra Costa County., • Cities: Oakland, Berkeley, Emeryville, San Leandro, Castro Valley, and Hayward. Supported Employment Responsibilities: • Provides coverage to consumers at their internship/job site during the absence of primary staff or during the initial training periods., • Provides direct services to consumers as needed including job coaching, pre-employment skills training, and assessment., • Assists consumers to grow in their educational and/or vocational skills by adapting training and support techniques to individual needs and learning styles., • Assists consumers to perform tasks crucial once employed or within internships to manage and report wages in regards to Social Security benefits as well as understand the impact of wages on benefits. (Initial wage reporting to Social Security, buying work clothing, union memberships, etc.), • Represents the agency and acts as liaison between the client, their family and friends, the employer, and other agencies (i.e. Supported and Independent Living agencies assisting the client)., • Provides assistance to the job developer with Tailored Day Services., • Assists to develop vocational sites to provide External Situational Assessments, provides support and evaluation during the assessment period and completes paperwork and final reports., • Brings all concerns to the supervisor and shares all development, progress or identified barriers with primary job coach or job developer., • Assists Director of Employment Services with billing and reports., • Assists with program evaluation, and service surveys., • Sets up files, performs filing, updates files and mailing lists for consumers and supports., • Attends all required training and staff meetings as assigned., • Provides outreach to employers to develop employment opportunities, as assigned., • Note any new barriers or support needs on monthly reports., • Help consumers take any pre-tests and get started with each course., • Help with understanding the content of the lessons, providing context, and elaborating on any points., • Assisting consumers with looking up challenging words/concepts and understanding them., • Providing and developing supplemental practice materials and personalized tools., • Practicing learned skills as they follow each topic to ensure understanding through custom created practice activities., • Assist consumers in taking online exams/tests and understanding the results., • Medical coverage for those working 30 hours a week or more, with two different providers for you to choose from., • Dental and vision coverage for both full-time and part-time staff., • Flexible Spending Account & Dependent Care FSA, Commuter, and Parking pre-tax benefits., • Voluntary Life, AD&D, Accident, Critical Illness, Hospital Indemnity, and Pet Insurance., • 403(b) retirement plan so you can invest in your future., • Education Assistance Fund, providing reimbursement for tuition, fees, and supplies for education and self-enrichment courses., • Membership in the Service Employees International Union (SEIU) Local 1021., • Many opportunities for training so you can feel confident in the work you do and prepare for future career opportunities., • Paid sick leave for all employees, and paid vacation for full-time employees, • Paid holidays for all Federal holidays., • Mileage reimbursement for on the job driving at $0.70 per mile., • EBI offers Additional Language Stipends for staff based on language fluency assessment and client/department/agency needs., • September is DSP Month, our special time to celebrate and thank our amazing staff! EBI hosts a fun-filled get-together with games, laughter, and plenty of opportunities to connect. The Public Service Loan Forgiveness program is a federal program that forgives student loan debt for nonprofit employees after 120 qualifying payments. Employees who work at least 30 hours per week for a governmental, 501(c)(3) nonprofit, or other qualifying nonprofit organization may apply to have the balance of their student loans forgiven (tax free) after making 120 monthly payments. East Bay Innovations is an equal opportunity employer. We will consider all applicants without regard to race, color, religion, national origin, ancestry, sex, gender, gender identity, physical or mental disability, medical condition, genetic information, marital status, age, sexual orientation, military or veteran status, or any other characteristic protected by applicable federal, state, or local law. Powered by JazzHR QDbFi3zc8I

Job DescriptionAbout Quizlet: At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. Our $1B+ learning platform serves tens of millions of students every month, including two-thirds of U.S. high schoolers and half of U.S. college students, powering over 2 billion learning interactions monthly. We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s Build the Future of LearningJoin us to design and deliver AI-powered learning tools that scale across the world and unlock human potential. About the Team (Applied AI): Our mission is to invent and deploy the next generation of intelligent, personalized, and adaptive learning experiences. We’re consolidating AI efforts across the company into a unified portfolio and are accountable for a disproportionate share of Quizlet’s growth and product differentiation. You’ll partner closely with Product, Data Science, and the AI & Data Platform to deliver an AI‑driven learning coach that’s recognized as best‑in‑class. About the Role: As an Applied AI Engineer, you will be working at the forefront of our AI strategy, shaping Quizlet’s AI develop in one of the two complementary domains: Personalization & Ranking – retrieval and ranking systems that match learners with the right content, experiences, and monetization moments across surfaces (search, feed, notifications, ads). Generative AI & Agentic Systems – LLM‑powered tutoring, content understanding/synthesis, and tools that boost learner outcomes and creator productivity. You will work on a variety of models and modeling systems (from Two‑Tower retrieval and multi‑task rankers to RAG/LLM pipelines), ensure robust evaluation and responsible deployment We’re happy to share that this is an onsite position in our San Francisco office. To help foster team collaboration, we require that employees be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company. We believe that this working environment facilitates increased work efficiency, team partnership, and supports growth as an employee and organization.In this role, you will: • Contribute to the technical roadmap for applied AI across personalization, ranking, search, recommendations, and GenAI/LLM systems; help connect modeling work to business metrics (engaged learners, conversion, retention, revenue), • Build components of end‑to‑end ML systems: candidate sourcing, embedding platforms & ANN retrieval, multi‑stage ranking (early/late), and value modeling with guardrails for fairness and integrity, • Implement LLM‑based features: build RAG pipelines, apply instruction‑/preference‑tuning techniques (e.g., SFT/DPO), optimize prompts, and improve latency/cost‑aware inference; contribute to offline evals + human‑in‑the‑loop and online success metrics, • Help develop "Learner 360" representations by working with behavior signals, explicit inputs, and conversational context to create robust embeddings reused across surfaces, • Support evaluation infrastructure: contribute to the eval harness for both ranking and generative systems (offline metrics like NDCG/AUC/BLEU/BERTScore; quality/safety scorecards), and help close the loop with online A/B experiments, • Ship reliable systems at scale: ensure training‑serving consistency, implement drift detection, follow canarying/rollback protocols, participate in on‑call rotation for model services, and maintain strong CI/CD for features & models, • Collaborate with and learn from senior ML/SWE teammates; write high‑quality code and follow best practices for experimentation rigor and reproducibility, • Work closely with Product, Design, Legal, and Data Science on objectives, tradeoffs, and responsible AI practices, • Stay current with ML research (RecSys, LLMs, multimodal) and propose new methods that could improve learner outcomesWhat you bring to the table:, • 8+ years of industry experience in applied ML/AI or ML‑heavy software engineering, • BS/MS in CS, ML, or related quantitative field (or equivalent experience), • Experience building ranking/personalization or search systems (retrieval, Two‑Tower/dual encoders, multi‑task rankers) and contributing to online metric improvements (e.g., CTR, session depth, retention), • Hands‑on experience with LLM/GenAI systems: data curation, fine‑tuning (SFT/PEFT, preference optimization), prompt engineering, evaluation, and productionization considerations (latency/cost/safety), • Strong skills in Python/PyTorch, data and feature engineering, distributed training/inference on GPUs, and familiarity with modern MLOps (model registry, feature stores, monitoring, drift), • Solid experiment design (offline/online), metrics literacy, and ability to translate product goals into modeling solutions, • Strong collaboration skills and eagerness to learn from senior engineers; some experience mentoring junior teammates is a plusBonus points if you have:, • EdTech or consumer mobile experience; conversational tutoring or learning science‑informed modeling, • Publications/open‑source with RecSys/LLMs (e.g., RecSys, KDD, NeurIPS, ICLR, ACL), or contributions to safety/guardrails tooling, • Experience building on a modern MLOps stack (feature mgmt, orchestration, streaming, online inference at scale)Compensation, Benefits & Perks:, • Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a starting base salary of $209,920 - $285,000, depending on location and experience, as well as company stock options, • Collaborate with your manager and team to create a healthy work-life balance, • 20 vacation days that we expect you to take!, • Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice), • Employer-sponsored 401k plan with company match, • Access to LinkedIn Learning and other resources to support professional growth, • Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits We strive to make everyone feel comfortable and welcome!We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership. We provide a transparent setting that gives a comprehensive view of who we are! In Closing: At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high-quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together.” Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion. As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us! To All Recruiters and Placement Agencies: At this time, Quizlet does not accept unsolicited agency resumes and/or profiles. Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet.#LI-FT We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.