{"schemaVersion":"jobsearcher.job.v1","id":"d6ec83a9166b3badcbe98448","url":"https://jobsearcher.com/jobs/d6ec83a9166b3badcbe98448","canonicalUrl":"https://jobsearcher.com/jobs/d6ec83a9166b3badcbe98448","title":"Machine Learning Engineer I, Network","description":"Location\nSan Francisco, CA\nEmployment Type\nFull time\nLocation Type\nOn-site\nDepartment\nEngineering\nCompensation\n$151K – $189K\nFor cash compensation, we set standard ranges for all U.S.-based roles based on function, level, and geographic location, benchmarked against similar stage growth companies. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors, including geographic location as well as candidate experience and expertise, and may vary from the amounts listed above.\n\nAbout Handshake\nHandshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.\nIn 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We've grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.\nWhy join Handshake now:\nShape how every career evolves in the AI economy, at global scale, with impact your friends, family, and peers can see and feel\nPartner with world-class AI labs, Fortune 500 companies, and the world’s leading educational institutions\nWork alongside engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders\nHelp build a massive, fast-growing business with billions in revenue\nAbout Handshake AI\nHuman data is the core infrastructure of AI advancement. Frontier AI labs currently improve model capabilities through various data-intensive post-training techniques. We believe spending on AI training data will increase by 3–5x over the next few years and continue growing as models expand into new domains. Handshake AI supports all frontier AI labs, working on their most complex data challenges at significant scale.\nAbout the Role\nHandshake is hiring a Machine Learning Engineer for the Network and Handshake AI Marketplace Relevance team. AI is transforming how students navigate their careers, and we’re committed to developing innovative, responsible AI-powered solutions that connect students with meaningful career opportunities.\nIn this role, you’ll build and improve the machine learning systems that power job search and recommendations, user understanding, personalized notifications, and core embedding models across the Handshake platform. You’ll work closely with experienced machine learning engineers, data scientists, product managers, and software engineers to develop models, run experiments, and deploy reliable ML solutions to production.\nThe team works with retrieval and ranking approaches including graph-based models, bi-encoders, semantic cross-encoders, and multi-stage rankers, supported by a data platform containing billions of data points. The team is also exploring emerging areas such as generative retrieval and post-training. Your work will directly contribute to improving marketplace outcomes while supporting Handshake’s commitment to explainability, fairness, and responsible AI.\nWhat You’ll Do\nBuild and improve machine learning models for search, recommendations, notifications, user understanding, and embeddings\nDevelop, test, and deploy models and supporting services in a production environment\nWork with large datasets to create features, train models, and evaluate performance\nContribute to retrieval, ranking, personalization, and experimentation systems\nMonitor production models and help improve their quality, reliability, latency, and scalability\nPartner with product, engineering, and data science to translate business and user needs into practical ML solutions\nParticipate in technical design discussions, code reviews, and team planning\nUse experimentation and marketplace metrics to measure the impact of your work\nContribute to team standards and best practices for model development, evaluation, and deployment\nDesired Capabilities\n3+ years of professional experience in machine learning, data science, software engineering, or a related field\nProficiency in Python and experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow\nExperience building, evaluating, and deploying machine learning models in production\nFamiliarity with one or more relevant areas, such as recommendations, search, personalization, ranking, NLP, deep learning, or LLMs\nUnderstanding of core ML concepts, including classification, regression, ranking, feature engineering, and model evaluation\nExperience working with data pipelines, experiment tracking, model monitoring, or other parts of the ML lifecycle\nStrong software engineering fundamentals and the ability to write reliable, maintainable code\nExperience working collaboratively with engineers, data scientists, product managers, and other cross-functional partners\nAbility to break down moderately complex problems, evaluate tradeoffs, and deliver solutions with support from senior team members\nA focus on measurable results and improving the end-user experience\nExtra Credit\nExperience with embedding-based retrieval, multi-stage ranking, graph-based models, or recommender systems\nExperience working with large-scale datasets or high-traffic cloud-based production systems\nFamiliarity with generative retrieval, LLM evaluation, or post-training techniques\nInterest in explainable AI, fairness, or responsible machine learning\nClear communication skills and an interest in contributing to team practices and technical standards\nPerks\nHandshake delivers benefits that help you feel supported—and thrive at work and in life.\nThe benefits below are for full-time US employees.\nOwnership: Equity in a fast-growing company\nFinancial Wellness: 401(k) match, competitive compensation, and financial coaching\nFamily Support: Paid parental leave, fertility benefits, and parental coaching\nWellbeing: Medical, dental, and vision coverage, mental health support, and a $500 wellness stipend\nGrowth: $2,000 learning stipend and ongoing development\nRemote & Office: Internet and commuting support, plus free lunch and gym access in our SF office\nTime Off: Flexible PTO, 15 holidays, and two flex days\nConnection: Team outings and referral bonuses\nExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.\nCompensation Range: $151K - $189K","company":"Handshake","rawCompany":"handshake","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-03T11:00:35.099Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer I, Network","description":"Location\nSan Francisco, CA\nEmployment Type\nFull time\nLocation Type\nOn-site\nDepartment\nEngineering\nCompensation\n$151K – $189K\nFor cash compensation, we set standard ranges for all U.S.-based roles based on function, level, and geographic location, benchmarked against similar stage growth companies. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors, including geographic location as well as candidate experience and expertise, and may vary from the amounts listed above.\n\nAbout Handshake\nHandshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.\nIn 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We've grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.\nWhy join Handshake now:\nShape how every career evolves in the AI economy, at global scale, with impact your friends, family, and peers can see and feel\nPartner with world-class AI labs, Fortune 500 companies, and the world’s leading educational institutions\nWork alongside engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders\nHelp build a massive, fast-growing business with billions in revenue\nAbout Handshake AI\nHuman data is the core infrastructure of AI advancement. Frontier AI labs currently improve model capabilities through various data-intensive post-training techniques. We believe spending on AI training data will increase by 3–5x over the next few years and continue growing as models expand into new domains. Handshake AI supports all frontier AI labs, working on their most complex data challenges at significant scale.\nAbout the Role\nHandshake is hiring a Machine Learning Engineer for the Network and Handshake AI Marketplace Relevance team. AI is transforming how students navigate their careers, and we’re committed to developing innovative, responsible AI-powered solutions that connect students with meaningful career opportunities.\nIn this role, you’ll build and improve the machine learning systems that power job search and recommendations, user understanding, personalized notifications, and core embedding models across the Handshake platform. You’ll work closely with experienced machine learning engineers, data scientists, product managers, and software engineers to develop models, run experiments, and deploy reliable ML solutions to production.\nThe team works with retrieval and ranking approaches including graph-based models, bi-encoders, semantic cross-encoders, and multi-stage rankers, supported by a data platform containing billions of data points. The team is also exploring emerging areas such as generative retrieval and post-training. Your work will directly contribute to improving marketplace outcomes while supporting Handshake’s commitment to explainability, fairness, and responsible AI.\nWhat You’ll Do\nBuild and improve machine learning models for search, recommendations, notifications, user understanding, and embeddings\nDevelop, test, and deploy models and supporting services in a production environment\nWork with large datasets to create features, train models, and evaluate performance\nContribute to retrieval, ranking, personalization, and experimentation systems\nMonitor production models and help improve their quality, reliability, latency, and scalability\nPartner with product, engineering, and data science to translate business and user needs into practical ML solutions\nParticipate in technical design discussions, code reviews, and team planning\nUse experimentation and marketplace metrics to measure the impact of your work\nContribute to team standards and best practices for model development, evaluation, and deployment\nDesired Capabilities\n3+ years of professional experience in machine learning, data science, software engineering, or a related field\nProficiency in Python and experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow\nExperience building, evaluating, and deploying machine learning models in production\nFamiliarity with one or more relevant areas, such as recommendations, search, personalization, ranking, NLP, deep learning, or LLMs\nUnderstanding of core ML concepts, including classification, regression, ranking, feature engineering, and model evaluation\nExperience working with data pipelines, experiment tracking, model monitoring, or other parts of the ML lifecycle\nStrong software engineering fundamentals and the ability to write reliable, maintainable code\nExperience working collaboratively with engineers, data scientists, product managers, and other cross-functional partners\nAbility to break down moderately complex problems, evaluate tradeoffs, and deliver solutions with support from senior team members\nA focus on measurable results and improving the end-user experience\nExtra Credit\nExperience with embedding-based retrieval, multi-stage ranking, graph-based models, or recommender systems\nExperience working with large-scale datasets or high-traffic cloud-based production systems\nFamiliarity with generative retrieval, LLM evaluation, or post-training techniques\nInterest in explainable AI, fairness, or responsible machine learning\nClear communication skills and an interest in contributing to team practices and technical standards\nPerks\nHandshake delivers benefits that help you feel supported—and thrive at work and in life.\nThe benefits below are for full-time US employees.\nOwnership: Equity in a fast-growing company\nFinancial Wellness: 401(k) match, competitive compensation, and financial coaching\nFamily Support: Paid parental leave, fertility benefits, and parental coaching\nWellbeing: Medical, dental, and vision coverage, mental health support, and a $500 wellness stipend\nGrowth: $2,000 learning stipend and ongoing development\nRemote & Office: Internet and commuting support, plus free lunch and gym access in our SF office\nTime Off: Flexible PTO, 15 holidays, and two flex days\nConnection: Team outings and referral bonuses\nExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.\nCompensation Range: $151K - $189K","datePosted":"2026-08-03T11:00:35.099Z","dateModified":"2026-08-03T11:00:35.099Z","hiringOrganization":{"@type":"Organization","name":"Handshake","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d6ec83a9166b3badcbe98448"},"url":"https://jobsearcher.com/jobs/d6ec83a9166b3badcbe98448"}}