Role Overview
Handshake is hiring a entry-level Machine Learning Engineer I. This is a full-time role in San Francisco. Part of Handshake's Lifecycle hiring, posted 3 weeks ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.
Salary Context
Salary is not disclosed in this posting. Market median for Junior-level Lifecycle roles is $82k-$104k (based on 21 comparable listings). Many employers share specifics during the interview process or after an initial screen.
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Job description
About Handshake
Handshake 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.
In 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.
Why join Handshake now:
- Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
- Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
- Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders
- Build a massive, fast-growing business with billions in revenue
About Handshake AI
Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.
About the Role
Handshake is hiring a Machine Learning Engineer I for the Growth Relevance team. AI is transforming how students navigate their careers, and we're committed to providing innovative, responsible AI-powered solutions that guide students from educational aspirations to meaningful career opportunities. In this role, you will contribute directly to this mission by developing, deploying, and enhancing machine learning systems focused on lifecycle optimization, personalized notifications, and monetization strategies.
You'll join a high-impact team leveraging cutting-edge ML infrastructure, including embedding-based retrieval, Graph Neural Networks, and multi-stage rankers built upon a robust data platform with billions of data points. Your work will drive critical marketplace metrics, enhance user engagement, and contribute to responsible AI practices around explainability, fairness, and quality.
What You'll Do
- Innovator: Develop and iterate on machine learning models and features that directly influence user experience across lifecycle, notifications, and monetization — with guidance from senior engineers.
- Collaborator: Partner with senior engineers, data scientists, and product managers to develop and iterate on machine learning models that improve product features and user experience.
- Learner: Grow your technical depth by working alongside experienced ML practitioners, picking up best practices in model development, experimentation, and production deployment.
Desired Capabilities
- Bachelor’s degree in Computer Science, Data Science, or a related field
- 3 years of experience in machine learning, data science, or a related area
- Proficient in Python, with hands-on experience in frameworks such as scikit-learn, PyTorch, or TensorFlow
- Strong foundation in core ML concepts, including classification, regression, ranking, and model evaluation
Extra Credit
- Master’s degree or currently pursuing an advanced degree in a relevant field
- Exposure to areas such as recommendations, personalization, NLP, deep learning, LLMs, or explainable AI
- Familiarity with the ML lifecycle (e.g., experiment tracking, model monitoring, feature pipelines)
- Experience with cloud platforms (GCP, AWS, or Azure)
- Clear communicator, able to translate technical work for diverse audiences
- Collaborative mindset with experience working cross-functionally with product, analytics, and engineering teams
Perks
Handshake delivers benefits that help you feel supported—and thrive at work and in life.
The below benefits are for full-time US employees.
🎯 Ownership: Equity in a fast-growing company
💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching
🍼 Family Support: Paid parental leave, fertility benefits, parental coaching
💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
📚 Growth: $2,000 learning stipend, ongoing development
💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office
🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days
🤝 Connection: Team outings & referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers http://joinhandshake.com/careers.
About Handshake
Handshake
joinhandshake.com
56 other open roles at Handshake on TryApplyNow.
Frequently Asked Questions
How do I apply for the Machine Learning Engineer I position at Handshake?
Use the Apply button above to submit your application directly to Handshake. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Machine Learning Engineer I position at Handshake located?
This position is based in San Francisco. Handshake has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Machine Learning Engineer I at Handshake earn?
Handshake has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Machine Learning Engineer I role at Handshake posted?
This role was posted on June 15, 2026 (24 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
Is the Machine Learning Engineer I role at Handshake entry-level?
Yes. This is an entry-level position. Strong candidates typically have 0-2 years of relevant work experience, internships, or significant project work. Read the full description for any specific qualification requirements Handshake has listed.
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