Machine Learning Engineer
Designs, develops, and deploys scalable ML systems using LLMs to process clinical data for healthcare applications. Requires 5+ years backend/cloud experience, Python fluency, and familiarity with ML frameworks; works onsite in Boston or NYC.
About the job
Responsibilities
- Translate state-of-the-art LLM research into production systems.
- Work with complex, large-scale clinical data (structured and unstructured) in cloud environments.
- Develop methods for high-quality results, including drift detection, observability tooling.
- Collaborate with product, engineering, and research teams to improve products.
- Ensure robust monitoring, logging, and error handling for deployed systems.
- Stay updated on ML/AI advancements.
- Cultivate ML engineering and product culture.
Requirements
- 5-7+ years in backend and cloud platform software development.
- Fluency in Python, Golang, Rust, or Java (Python used).
- Familiarity with modern ML/LLM techniques and frameworks.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or related field.
- Experience developing scalable, data-centric enterprise software.
- Strong problem-solving, attention to detail, communication skills.
Nice-to-Haves
- 0-to-1 development of end-to-end ML systems (design, training, inference, deployment, monitoring; bonus for LLMs).
Compensation
- $210,000-250,000/year base, plus stock options (dependent on experience, fit, location).
Skills
Python, LLMs, Machine Learning, Cloud Platforms, Go, Rust, Java, Model Monitoring, Drift Detection, Observability Tooling
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