onsite
Machine Learning Engineer - OPTUM GmbH
ML Engineer
Develop and deploy production‑ready ML models using Python, TensorFlow/PyTorch, and AWS services. Collaborate with data scientists and DevOps to scale solutions, ensuring performance, reliability, and maintainability.
About the role
Key Responsibilities
- Design, implement, and optimize machine learning models for real‑world applications using Python, TensorFlow, and PyTorch.
- Deploy models to AWS infrastructure (SageMaker, ECS, Lambda) and maintain CI/CD pipelines with Docker and GitHub Actions.
- Collaborate with data engineering teams to ingest, clean, and transform large datasets using SQL and Spark.
- Monitor model performance, conduct A/B testing, and iterate on feature engineering to improve accuracy and latency.
- Document model architecture, training procedures, and deployment steps for internal knowledge sharing.
Requirements
- 3+ years of experience in machine learning engineering or related field.
- Strong proficiency in Python, with hands‑on experience in TensorFlow or PyTorch.
- Hands‑on experience deploying models on AWS (SageMaker, ECS, Lambda) and containerizing with Docker.
- Solid understanding of data pipelines, SQL, and big‑data tools (Spark, Hadoop).
- Excellent problem‑solving skills and ability to work collaboratively in cross‑functional teams.
Skills
pythonmachine learningtensorflowpytorchawsdockersql