onsite
Machine Learning Engineer - Parship
ML Engineer
Design, develop, and deploy machine learning models using Python, TensorFlow, and PyTorch on AWS infrastructure to solve complex data problems and deliver high‑impact solutions.
About the role
Key Responsibilities
- Build and train end‑to‑end machine learning pipelines from data ingestion to model deployment.
- Collaborate with data scientists and product teams to translate business requirements into scalable ML solutions.
- Optimize model performance and resource usage on AWS services such as SageMaker, EC2, and S3.
- Implement robust monitoring, logging, and A/B testing frameworks to ensure model reliability.
- Document model architecture, experiments, and best practices for reproducibility.
Requirements
- Strong programming skills in Python and experience with TensorFlow or PyTorch.
- Hands‑on experience deploying models on AWS (SageMaker, Lambda, ECS).
- Solid understanding of data preprocessing, feature engineering, and model evaluation.
- Experience with CI/CD pipelines for ML workflows.
- Excellent problem‑solving skills and ability to work in a fast‑paced environment.
Skills
pythonmachine learningtensorflowpytorchaws