Machine Learning Engineer
Role details
Job location
Tech stack
Job description
This is a hands-on engineering role focused on building and deploying production-grade AI solutions in the life sciences domain. You will work on scalable implementations of AI/ML models, transforming prototypes into robust solutions that deliver real impact for global healthcare clients.
What You'll Do
- Design, implement, and optimize end-to-end ML pipelines for healthcare applications.
- Work on a variety of AI/ML projects, including opportunities to apply generative AI and foundation models where relevant.
- Build and maintain production-ready algorithms that handle complex, high-dimensional data.
- Collaborate with cross-functional teams to translate business needs into scalable AI solutions.
- Ensure model performance, reliability, and compliance for deployment in regulated environments.
Requirements
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2-4 years of experience delivering ML solutions in a commercial or production environment (not just academic projects).
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Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow).
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Hands-on experience with large datasets and cloud-based deployment (AWS, Azure, GCP).
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Familiarity with modern ML techniques and interest in emerging technologies such as generative AI and foundation models.
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Degree in Computer Science, Machine Learning, or related field.
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Ability to work in a fast-paced environment and bridge technical and business requirements. Nice to Have
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Experience with MLOps tools (Docker, Kubernetes, MLflow).
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Knowledge of life sciences or healthcare data.