Six Figure Work

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Machine Learning Engineer

Handshake

Company websitejoinhandshake.com (Handshake, opens in new tab)

Base salary $150K  to $189K

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (44 min ago) · observed since

About this job

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 0to~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 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

  • 1-3 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

  • Experience with deploying and evaluating agentic workflows

  • 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

Source: Handshake on Ashby · View original posting (opens in new tab)

This range next to 6 other live Handshake roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Handshake roles with the nearest advertised base floor
RolePublished base
Machine Learning Engineer (this listing)$150K - $189K
Senior Marketing Manager - Fellows$152K - $190K
Senior Product Marketing Manager, Handshake AI$152K - $190K
Forward Deployed Engineer, Enterprise AI$155K - $170K
GTM Engineer$156K - $195K
Senior Partner Insights Manager - EDU$144K - $180K
Strategic Projects Lead$160K

Same $100K to $400K scale as every card. All Handshake roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-08
Where this pay comes from

Location as the employer wrote it: San Francisco, CA

USD 150,000 – 189,000 · 1 YEAR · Salary

Method
Structured pay field published by the employer
Checked
Rule set
us-base-v2

The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.