onsite
AI Systems Engineer - Flexscale
Systems Engineer
Mid‑senior AI Systems Engineer responsible for designing, deploying, and maintaining scalable machine‑learning pipelines and intelligent services on cloud infrastructure, leveraging Python, AWS, Docker, and Kubernetes.
About the role
Key Responsibilities
- Design, develop, and operationalize end‑to‑end machine‑learning models and data pipelines supporting loan origination, underwriting, and servicing workflows.
- Build and maintain containerized micro‑services on Docker and Kubernetes, ensuring high availability and low latency for AI‑driven APIs.
- Implement CI/CD pipelines using tools such as GitHub Actions or Jenkins to automate testing, deployment, and monitoring of AI services.
- Collaborate with data scientists, product owners, and infrastructure teams to translate business requirements into scalable technical solutions.
- Monitor performance, troubleshoot production issues, and continuously optimize models and infrastructure for cost and efficiency on AWS.
Requirements
- 5+ years of professional experience in software engineering or AI systems development.
- Strong proficiency in Python and modern ML frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn).
- Hands‑on experience with AWS services (EC2, S3, SageMaker, Lambda) and container orchestration using Docker and Kubernetes.
- Proven ability to build CI/CD pipelines and implement MLOps best practices.
- Solid understanding of Linux environments, RESTful API design, and performance monitoring tools.
Skills
pythonmachine learningawsdockerkubernetescicd