remote
Senior Machine Learning Engineer - accurx
ML Engineer
Lead the design and deployment of scalable ML solutions for a nationwide digital health platform, leveraging Python, TensorFlow, and AWS to deliver real‑time insights and automation across patient care workflows.
About the role
Key Responsibilities
- Architect and implement end‑to‑end machine learning pipelines that power features such as patient triage, self‑booking, and automated questionnaire analysis.
- Collaborate with data scientists, backend engineers, and product managers to translate business requirements into robust ML models and services.
- Deploy models to production using Docker, Kubernetes, and AWS SageMaker, ensuring high availability, scalability, and compliance with healthcare data regulations.
- Monitor model performance, conduct A/B testing, and iterate on algorithms to improve accuracy and user experience.
- Mentor junior engineers and promote best practices in code quality, testing, and documentation.
Requirements
- 5+ years of experience building production‑grade machine learning systems in a cloud environment.
- Proficiency in Python, TensorFlow or PyTorch, and experience with containerization (Docker) and orchestration (Kubernetes).
- Strong background in AWS services such as SageMaker, S3, Lambda, and IAM.
- Excellent problem‑solving skills and ability to work in a fast‑paced, cross‑functional team.
- Experience with healthcare data standards (FHIR, HL7) and data privacy regulations is a plus.
Skills
pythonmachine learningawstensorflowpytorchdockerkubernetes