Key Responsibilities
- Develop and deploy machine learning models for production environments
- Design and implement scalable ML pipelines for training and inference
- Optimize models for performance, latency, and resource efficiency
- Collaborate with data scientists to translate research into deployable solutions
- Monitor model performance and implement continuous improvement strategies
- Ensure reproducibility and versioning of ML experiments
Requirements
- 3+ years of experience in machine learning engineering
- Proficiency in Python and ML frameworks (TensorFlow, PyTorch)
- Experience with MLOps tools (Docker, Kubernetes, MLflow)
- Strong understanding of algorithms and data structures
- Familiarity with cloud platforms and big data technologies