onsite
Forward Deployed AI Engineer - UDG
AI Engineer
Lead end‑to‑end AI solutions in production, collaborating with cross‑functional teams to design, deploy, and scale machine learning models on AWS using Docker and Kubernetes, while ensuring robust CI/CD pipelines and high‑quality data pipelines.
About the role
Key Responsibilities
- Design, develop, and deploy production‑ready machine learning models using Python and AWS services.
- Collaborate with data scientists, product managers, and DevOps to translate research into scalable, maintainable solutions.
- Build and maintain containerized (Docker) and orchestrated (Kubernetes) environments for model serving.
- Implement CI/CD pipelines to automate testing, deployment, and monitoring of AI workloads.
- Optimize model performance and resource utilization, ensuring cost‑effective operation on cloud infrastructure.
- Provide technical mentorship and code reviews to junior engineers.
Requirements
- 5+ years of experience in AI/ML engineering with a strong Python background.
- Proven track record of deploying models to production on AWS (SageMaker, ECS, EKS).
- Hands‑on experience with Docker, Kubernetes, and CI/CD tools (GitHub Actions, Jenkins, ArgoCD).
- Deep understanding of data pipelines, feature engineering, and model monitoring.
- Excellent communication skills and ability to work in a fast‑paced, collaborative environment.
Skills
pythonmachine learningawsdockerkubernetescicd