onsite
Senior Machine Learning Solutions Architect - Empower Retirement
ML Engineer
Lead the design and deployment of scalable ML solutions on AWS, leveraging Python, TensorFlow, and Kubernetes to deliver high‑impact financial products.
About the role
Key Responsibilities
- Architect end‑to‑end ML pipelines from data ingestion to model serving on AWS.
- Collaborate with data scientists to translate research prototypes into production‑ready services.
- Design and maintain scalable Kubernetes clusters and CI/CD workflows for model deployment.
- Implement robust monitoring, logging, and automated retraining mechanisms.
- Provide technical mentorship to cross‑functional teams and drive best practices in ML Ops.
Requirements
- 5+ years of experience building production ML systems in a cloud environment.
- Proficiency in Python, TensorFlow/PyTorch, and AWS services (SageMaker, ECS, EKS, S3, Lambda).
- Strong background in data engineering, SQL, and big data technologies.
- Hands‑on experience with Kubernetes, Helm, and CI/CD pipelines.
- Excellent communication skills and a collaborative mindset.
Skills
pythonmachine learningawstensorflowkubernetes