Staff Machine Learning Engineer

the team ships models into production. You'll 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 points. In addition,

the team is investing into areas of generative retrieval and post-training. Your work will directly move the marketplace's core metrics, and you'll be a key voice in how Handshake approaches explainability, fairness, and quality as we scale responsible AI across the product.

What You'll 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 team's 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: $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 .

A meeting lands on your calendar

If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.