Our startup client is seeking a curious and collaborative ML Research Engineer who thrives at the intersection of cutting-edge research and meaningful healthcare applications. As part of our innovative team, you'll design, train, and deploy machine learning solutions that directly improve patient outcomes and clinical workflows.

 **What you'll do**

- Design and train novel ML models, leveraging GPU clusters and state-of-the-art ML tools like PyTorch.
- Analyze experimental results rigorously, developing robust and scalable solutions.
- Collaborate closely with clinicians, ML researchers, and product engineers to ensure practical and impactful solutions.
- Balance exploration of new ML techniques with the realities of healthcare data and applications.
- Communicate your findings clearly through technical documentation, research papers, and engaging whiteboard sessions.

 **We'd love to hear from you if you have**

- 2+ years of ML research experience, with proficiency in PyTorch and Python.
- Strong software engineering skills and experience deploying ML models on GPU infrastructure.
- A solid mathematical understanding of machine learning algorithms.
- A track record of written technical documentation and/or research papers.
- A hypothesis-driven approach to research, complemented by meticulous evaluation.
- Appreciation for the complexities and significance of healthcare data and high-stakes ML applications.
- Excellent communication skills, with a knack for explaining complex concepts simply and clearly.

**Bonus points if you have**

- Prior experience in healthcare or medical domains.
- Experience creating or curating healthcare datasets.
- Familiarity with medical terminology and clinical workflows.
- Experience with MLOps: CI/CD pipelines, model monitoring, versioning, and continuous retraining.
- Familiarity with state-of-the-art ML research.