SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Handshake is hiring a Machine Learning Engineer for the Network and Marketplace Relevance team. The role focuses on building and improving machine learning systems that power job search, recommendations, personalized notifications, and core embedding models across the Handshake platform.
You'll work with retrieval and ranking approaches including graph-based models, bi-encoders, semantic cross-encoders, and multi-stage rankers, supported by a data platform containing billions of data points. The team is exploring emerging areas such as generative retrieval and post-training.
Key responsibilities include:
- Build and improve ML models for search, recommendations, notifications, user understanding, and embeddings
- Develop, test, and deploy models and supporting services in production
- Work with large datasets to create features, train models, and evaluate performance
- Contribute to retrieval, ranking, personalization, and experimentation systems
- Monitor production models and improve quality, reliability, latency, and scalability
- Partner with product, engineering, and data science teams to translate business needs into ML solutions
- Participate in technical design discussions, code reviews, and team planning
- Use experimentation and marketplace metrics to measure impact
- Contribute to team standards for model development, evaluation, and deployment
Required qualifications:
- 3+ years of professional experience in machine learning, data science, software engineering, or related field
- Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow)
- Experience building, evaluating, and deploying ML models in production
- Familiarity with recommendations, search, personalization, ranking, NLP, deep learning, or LLMs
- Understanding of core ML concepts: classification, regression, ranking, feature engineering, model evaluation
- Experience with data pipelines, experiment tracking, model monitoring
- Strong software engineering fundamentals and ability to write reliable, maintainable code
- Collaborative experience with engineers, data scientists, product managers
- Ability to break down complex problems and deliver solutions with senior support
- Focus on measurable results and user experience
Desirable experience includes embedding-based retrieval, multi-stage ranking, graph-based models, recommender systems, large-scale datasets, high-traffic production systems, generative retrieval, LLM evaluation, post-training techniques, explainable AI, and fairness in machine learning.
Handshake powers 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. The company recently launched Handshake AI, a rapidly growing AI data business supporting frontier AI labs with data-intensive post-training techniques.
