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
1. Design and train novel ML models, leveraging GPU clusters and state-of-the-art ML tools like PyTorch.
2. Analyze experimental results rigorously, developing robust and scalable solutions.
3. Collaborate closely with clinicians, ML researchers, and product engineers to ensure practical and impactful solutions.
4. Balance exploration of new ML techniques with the realities of healthcare data and applications.
5. Communicate your findings clearly through technical documentation, research papers, and engaging whiteboard sessions.
We'd love to hear from you if you have
1. 2+ years of ML research experience, with proficiency in PyTorch and Python.
2. Strong software engineering skills and experience deploying ML models on GPU infrastructure.
3. A solid mathematical understanding of machine learning algorithms.
4. A track record of written technical documentation and/or research papers.
5. A hypothesis-driven approach to research, complemented by meticulous evaluation.
6. Appreciation for the complexities and significance of healthcare data and high-stakes ML applications.
7. Excellent communication skills, with a knack for explaining complex concepts simply and clearly.
Bonus points if you have
1. Prior experience in healthcare or medical domains.
2. Experience creating or curating healthcare datasets.
3. Familiarity with medical terminology and clinical workflows.
4. Experience with MLOps: CI/CD pipelines, model monitoring, versioning, and continuous retraining.
5. Familiarity with state-of-the-art ML research.
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