Machine Learning Engineer I, Network

About the role

Handshake is seeking a Machine Learning Engineer to join the Network and Handshake AI Marketplace Relevance team. This role focuses on developing and enhancing AI-driven solutions that connect students with career opportunities. You will contribute to the core ML systems that power job search, recommendations, and user personalization across the platform.

Key facts

What you'll do

• Build and refine machine learning models for search, recommendations, notifications, user understanding, and platform embeddings.
• Develop, test, and deploy models and supporting services into a production environment.
• Work with extensive datasets to create features, train models, and assess performance.
• Contribute to systems for retrieval, ranking, personalization, and experimentation.
• Monitor production models to enhance their quality, reliability, latency, and scalability.
• Collaborate with product, engineering, and data science teams to translate user needs into ML solutions.
• Participate in technical design discussions, code reviews, and team planning.
• Use experimentation and marketplace metrics to measure the impact of your work.
• Help establish team standards and best practices for model development, evaluation, and deployment.

Requirements

• 3+ years of professional experience in machine learning, data science, software engineering, or a related field.
• Proficiency in Python and experience with ML frameworks like scikit-learn, PyTorch, or TensorFlow.
• Experience building, evaluating, and deploying machine learning models in a production setting.
• Familiarity with one or more areas such as recommendations, search, personalization, ranking, NLP, deep learning, or LLMs.
• Understanding of core ML concepts including classification, regression, ranking, feature engineering, and model evaluation.
• Experience with data pipelines, experiment tracking, or model monitoring.
• Strong software engineering fundamentals and the ability to write reliable, maintainable code.
• Experience collaborating with engineers, data scientists, product managers, and other cross-functional partners.
• Ability to break down moderately complex problems, evaluate tradeoffs, and deliver solutions with support.
• A focus on measurable results and improving the end-user experience.

Nice to have

• Experience with embedding-based retrieval, multi-stage ranking, graph-based models, or recommender systems.
• Experience working with large-scale datasets or high-traffic cloud-based production systems.
• Familiarity with generative retrieval, LLM evaluation, or post-training techniques.
• Interest in explainable AI, fairness, or responsible machine learning.
• Clear communication skills and an interest in contributing to team practices and technical standards.

Skills & tools

• Python
• scikit-learn
• PyTorch
• TensorFlow
• ML frameworks
• Data pipelines
• Experiment tracking
• Model monitoring

Practical notes

This role is for full-time US employees. Benefits include equity, 401(k) match, paid parental leave, fertility benefits, medical/dental/vision coverage, mental health support, a $500 wellness stipend, a $2,000 learning stipend, flexible PTO, 15 holidays, two flex days, internet and commuting support, and free lunch and gym access in the SF office.