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 1600 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. Weve 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 worlds top educational institutions

• Work alongside 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 35x 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 Staff Machine Learning Engineer for the Network and Handshake AI Marketplace Relevance team. AI is transforming how students navigate their careers and were committed to providing innovative responsible AI-powered solutions that guide students from educational aspirations to meaningful career opportunities.

In this role you will set the technical direction for the systems that power core embedding models consumer job search & recommendations user understanding and personalized notifications across the Handshake platform. Youll operate as a force multiplier architecting the ML infrastructure that the broader Relevance org builds on and raising the technical bar for how the team ships models into production.

Youll own the roadmap for a suite of systems built on multiple retrieval models Graph Neural Network bi-encoders semantic cross-encoders with multi-stage rankers running on a data platform with billions of data addition the team is investing into areas of generative retrieval and post-training. Your work will directly move the marketplaces core metrics and youll be a key voice in how Handshake approaches explainability fairness and quality as we scale responsible AI across the product.

What Youll Do

Architect: Define the technical strategy and system design for ML models and infrastructure spanning search and recommendation notifications generative retrieval and core embeddings making build-vs-buy architecture and platform decisions with company-wide impact.

Force Multiplier: Set technical standards and best practices for model development experimentation and production deployment; mentor and elevate engineers and data scientists across the team.

Cross-functional Leader: Partner with engineering leadership product and data science to translate ambiguous business problems into a clear technical roadmap and drive alignment across stakeholders on priorities and tradeoffs.

Operator: Get hands-on where it matters most building and shipping the highest-leverage models and systems yourself and unblocking the team on the hardest technical problems.

Desired Capabilities

• 8 years of experience in machine learning data science or a related field with a track record of owning large-scale production ML systems end-to-end

• Deep expertise in Python and ML frameworks such as scikit-learn PyTorch or TensorFlow

• Experience in recommendations personalization NLP deep learning LLMs or explainable AI

• Deep familiarity with the ML lifecycle (experiment tracking model monitoring feature pipelines) at scale

• Demonstrated ability to architect and scale ML infrastructure embedding-based retrieval ranking systems GNNs or similar in a high-traffic cloud based production environment

• Strong foundation in core ML concepts (classification regression ranking model evaluation) with the judgment to know when and how to apply them

• Experience setting technical direction across teams and mentoring senior and mid-level engineers

• Track record of driving measurable business impact through ML systems at scale

• Experience with Generative Retrieval and LLM Post Training recipes is a plus.

Extra Credit

• A track record as a clear persuasive communicator who can align technical and non-technical stakeholders around a shared roadmap

• Experience building or scaling a teams technical practices and standards from the ground up

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: $2000 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 Experience:

Staff IC