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Senior Machine Learning Engineer
במקום העבודהמשרה מלאהAI & Machine LearningHealthcare Technology
Join a health technology company developing predictive intelligence for cardiovascular risk, user engagement, and personalized health recommendations. Own machine learning models from research and data exploration through production deployment and monitoring.
תחומי אחריות
- Lead end-to-end development of predictive machine learning models across engagement and clinical risk domains.
- Explore data, engineer features, train and validate models, and manage deployment and ongoing monitoring.
- Design models using statistical methods, feature selection, uncertainty quantification, and result interpretation.
- Write clean, tested, maintainable, and scalable production Python code.
- Use AI coding assistants for development, code review, and documentation.
- Collaborate with product managers, data engineers, and software engineers to develop measurable data-driven solutions.
- Research and implement supervised and unsupervised learning, causal inference, deep learning, and reinforcement learning techniques.
- Contribute to MLOps infrastructure, including model serving, versioning, evaluation pipelines, and monitoring.
- Design and interpret A/B tests and other experiments measuring model, feature, and intervention impact.
דרישות
- 5+ years of experience developing, deploying, and maintaining production machine learning models.
- Bachelor’s degree in statistics, computer science, applied mathematics, engineering, or a related quantitative field.
- Strong expertise in statistics and probability, including inference, hypothesis testing, Bayesian methods, causal inference, and experimental design.
- Strong production software engineering skills in Python, including testing, version control, and reproducibility.
- Proficiency with AI coding assistants in development workflows.
- Expertise with frameworks such as PyTorch, scikit-learn, XGBoost, or LightGBM.
- Experience with end-to-end machine learning pipelines, feature engineering, model registries, and deployment tooling.
- Ability to communicate complex statistical and technical findings to technical and non-technical stakeholders.
יתרון
- Experience with AWS, Docker, Kubernetes, or MLOps platforms.
- Experience with healthcare or clinical datasets, including wearable, EMR, or claims data.
- Experience with recommendation systems, reinforcement learning, or advanced causal inference.