Senior Machine Learning Engineer

The Ranking & Relevance team’s mission is to help every patient find the right provider for their needs. We are building the matching system that powers this connection, from search and discovery to ranking and personalization. Our goal is to combine cutting-edge machine learning with a deep understanding of patient and provider experience.

We are looking for a Senior Machine Learning Engineer to be a core contributor to Headway's ranking and relevance systems. You will design, build, and ship ML models that determine how patients discover and connect with therapists — using search, recommendation, and personalization techniques to improve matching quality across the care journey.

In this role, you will work with significant autonomy on scoped problem areas, contribute to technical direction, and collaborate closely with product, engineering, and data science to drive measurable outcomes for patients and providers.

At Headway, one of our most important challenges is ensuring that patients find the right therapist quickly and effectively. We are investing deeply in search, ranking, and relevance systems powered by machine learning. As a Senior Machine Learning Engineer, you will focus on:

• →Matching and ranking: Build and iterate on ML models that power how patients discover and connect with providers — from candidate generation to final ranking.
• →Personalization: Leverage patient signals, provider attributes, and outcomes data to improve matching accuracy and relevance over time.
• →Model development end-to-end: Own the full lifecycle of models you build — from offline evaluation and experimentation to production deployment and monitoring.
• →Experimentation: Design and analyze A/B tests, define the right offline proxies and online metrics, and translate results into product decisions.
• →Cross-functional collaboration: Partner with product managers, software engineers, and data scientists to scope problems, align on success metrics, and ship improvements that move the needle for patients.
• →Raising the bar: Contribute to ML best practices on the team — through code reviews, documentation, and sharing what you learn from the systems you build.

• You have 5+ years of experience in applied ML roles, with at least 3 years of meaningful hands-on modeling work in ranking, relevance, recommendations, search, or personalization.
• You are fluent in Python and experienced with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or CatBoost.
• You have taken ML models from prototype to production and understand what it takes to make them reliable, maintainable, and performant at scale.
• You are comfortable designing and running A/B experiments, selecting appropriate metrics, and interpreting results with rigor.
• You bring product intuition alongside technical depth — you care about making the patient experience meaningfully better, not just improving an offline metric.
• You work well in collaborative, cross-functional environments and can communicate technical tradeoffs clearly to non-ML stakeholders.

• Experience with search, discovery, matching systems or consumer facing personalization.
• Familiarity with modern retrieval techniques (vector search, embeddings, semantic search).
• Exposure to ML infrastructure such as feature stores, model monitoring, and retraining pipelines.
• Experience with Metaflow, SageMaker, and Outerbounds.
• Background in healthcare, marketplace, or other B2C domains where user-provider or user-product fit is the core product problem.

After you apply to Headway, here are some details of what to expect during the interview process.

1. Initial screen: You’ll connect with someone in recruiting so you can learn more about the team, Headway’s mission and exciting growth, and we can get a better idea of your background.
2. First round: You’ll meet with an engineer on the team to do some live coding and learn more about the engineering team.
3. Final rounds: You’ll meet several more team members for technical and non-technical interviews and leave with a fuller picture of what it’s like to work at Headway.
4. References and the offer: Our favorite part of the process. We’ll send over all of the details, including specifics on employee equity, and congratulatory messages from excited future team members.