Senior Machine Learning Engineer - Growth Relevance

Salary: $220K - $260K Employment Type: FullTime

Position Overview

Handshake is seeking a Senior Machine Learning Engineer to join the Growth Relevance team. This role is pivotal in leveraging AI to transform how students navigate their careers, providing innovative and responsible AI-powered solutions that connect educational aspirations with meaningful career opportunities. The successful candidate will develop, deploy, and enhance machine learning systems focused on lifecycle optimization, personalized notifications, and monetization strategies.

You will be part of a high-impact team utilizing cutting-edge ML infrastructure, including embedding-based retrieval, Graph Neural Networks, and multi-stage rankers, all built upon a robust data platform with billions of data points. Your contributions will directly impact critical marketplace metrics, improve user engagement, and uphold responsible AI practices concerning explainability, fairness, and quality.

Your Role

• Technical Leader: Drive technical solutions, elevate engineering practices, foster cross-team collaboration, and mentor colleagues to deliver impactful ML-driven products.
• Innovator: Develop and optimize machine learning models and systems that directly influence user experience across lifecycle, notifications, and monetization.
• Collaborator: Partner closely with product managers, data scientists, and engineers to design, execute, and iterate on ML-driven user experiences and experiments, providing key insights to inform strategic product decisions.

Your Experience

You are a hands-on ML engineer with a proven track record in identifying complex problems, crafting thoughtful technical solutions, and executing projects from conception to deployment. You possess a strong balance of technical expertise and collaboration skills, a relentless focus on user outcomes, and the ability to thrive in ambiguity by making informed, data-driven decisions.

• 3+ years of industry experience building and deploying production ML systems.

Bonus Areas of Expertise

• Hands-on experience developing, deploying, and optimizing web-scale ML systems.
• Experience with ML lifecycle management, personalization systems, notification optimization, and/or monetization-driven algorithms.
• Background in one or more ML areas: recommendations, personalization, NLP, deep learning, LLM integration, or explainable AI.
• Familiarity building scalable ML applications using cloud infrastructure (GCP, AWS, Azure).