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Machine Learning Engineer - Digital Transformation - Arcfield
ML Engineer
Design and deploy machine‑learning pipelines that drive digital transformation, leveraging Python, AWS cloud services, and containerized workflows to deliver scalable, data‑driven solutions.
About the role
Key Responsibilities
- Develop, train, and optimize machine‑learning models for production use cases.
- Build end‑to‑end data pipelines using Python and cloud services (AWS S3, Lambda, SageMaker).
- Containerize applications with Docker and orchestrate deployments for reliable scaling.
- Collaborate with cross‑functional teams to translate business requirements into technical specifications.
- Monitor model performance in production and implement continuous improvement processes.
Requirements
- 3+ years of experience in Python development and machine‑learning model lifecycle management.
- Proficiency with AWS services (S3, EC2, SageMaker, Lambda) and infrastructure‑as‑code tools.
- Strong background in data engineering concepts, including ETL, data warehousing, and streaming.
- Hands‑on experience with Docker (or similar container platforms) and CI/CD pipelines.
- Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degree preferred.
Skills
pythonmachine learningawsdocker