ML Research Engineer
Designs, develops, and deploys scalable ML systems and backend infrastructure for healthcare applications, translating LLM research into production while handling large-scale clinical data. Requires 3+ years ML backend experience, 5+ years software development, and backend languages like Python.
About the job
Responsibilities
- Architect efficient, secure, reliable, and performant ML pipelines and infrastructure.
- Design, develop, and maintain scalable/data-centric backend infrastructure for our product.
- Translate start-of-the-art LLM research into production.
- Work with complex, large-scale, real-world clinical data in a cloud-based environment.
- Develop methods and features to ensure high-quality results for production models (drift detection, observability tooling).
- Collaborate with product, engineering, and research teams to improve products and build next-generation ML for healthcare.
- Build scalable infrastructure for model development and deployment pipelines, CI/CD, testing/experimentation.
- Ensure robust monitoring, logging, and error handling for deployed systems.
- Stay updated on latest advancements in machine learning and AI.
Requirements
- 3+ years of experience in building ML-native backend infrastructure.
- 5-7+ years of experience in backend and cloud platform software development.
- Fluency in one or more backend programming languages including Python, Golang, Rust, Java.
- Familiarity with modern ML/LLM techniques and frameworks.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or related field.
- Experience in 0-to-1 development of end-to-end ML systems (design, training, inference, deployment, monitoring; bonus for LLMs).
- Experience developing and maintaining performant, scalable, data-centric enterprise software products.
- Strong problem-solving skills and attention to detail.
- Excellent communication skills.
Compensation
- Expected range: $160,000-200,000, plus stock options (dependent on experience, fit, and location).
Skills
Python, Go, Rust, Java, Machine Learning, LLMs, Ml Pipelines, Cloud Platforms, CI/CD, Model Monitoring
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