Machine Learning Engineer (Model Dev)

📋 Description

• Develop and evaluate AI-based biomarkers using multimodal datasets, including whole-slide images
• Contribute to self-supervised foundation models and downstream machine-learning systems, including
• Design and evaluate approaches that improve model robustness and reproducibility across scanners
• Investigate model interpretability techniques to explain predictions, strengthen clinician trust
• Build and enhance tools, workflows, and pipelines that enable efficient, reproducible
• Conduct rigorous model evaluation, analyze experimental results, troubleshoot model behavior, and

🎯 Requirements

• At least 1 year of experience developing machine-learning or deep-learning models using PyTorch
• Familiarity with oncology and biomarker development, including cancer biology, treatment pathways
• Experience working with real-world datasets and applying appropriate metrics and validation
• Strong Python programming skills and familiarity with modern software-engineering practices
• Ability to analyze experimental results, investigate model behavior, troubleshoot technical issues
• Strong collaboration skills and the ability to work effectively with machine-learning engineers

🎁 Benefits

• Base salary of $140,000–$180,000 per year, depending on experience, qualifications, and other
• Equity as a core component of the overall compensation package.
• 401(k) plan with employer matching.
• Unlimited paid time off (PTO).
• Remote work environment.
• Opportunity to work on challenging medical-AI problems with potential to improve cancer diagnosis