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Senior Machine Learning Engineer
HybridFull-timeAI & Machine LearningDigital Health
Join a machine learning team building and operating real-time algorithms for a digital health platform serving the US healthcare market. The role is based in Tel Aviv with a hybrid schedule that includes two days working from home.
Responsibilities
- Own machine learning models end to end, from architecture and deployment to maintenance in high-throughput production environments.
- Build scalable ML infrastructure, automated training and serving pipelines, and feature stores across distributed cloud environments.
- Develop MLOps practices for CI/CD, ongoing model evaluation, drift detection, and production monitoring.
- Apply machine learning methods to clinical, sensory, and behavioral data, including supervised and unsupervised learning, gradient boosting, causal inference, and reinforcement learning.
- Collaborate with software and data engineers and product managers to deliver low-latency, reliable, scalable models.
Requirements
- At least 5 years of hands-on experience as a Machine Learning Engineer.
- Experience building and serving machine learning models in high-scale, real-time production environments.
- Practical experience architecting and deploying cloud systems on AWS, GCP, or Azure, including SaaS architectures.
- Strong Python software engineering skills and experience with automated ML pipelines, MLOps tooling, and CI/CD.
- Hands-on expertise with scikit-learn, XGBoost, LightGBM, and distributed data frameworks.
- Understanding of model serving, performance optimization, monitoring, and debugging in production.
- Fluent English communication skills.
Nice to have
- Experience in an agile, fast-paced startup environment.