Machine Learning Engineer supporting the Enterprise Machine Learning team in developing advanced solutions. Collaborating with stakeholders and driving data science initiatives in a hybrid work environment.
About the role
- Senior Platform/MLOps Engineer designing and maintaining scalable infrastructure for AI at Bright Machines. Join a team transforming manufacturing through intelligent automation.
Responsibilities
- Design, implement, and maintain reliable, scalable, and secure infrastructure, applications, and tooling, with a focus on our ML/AI pipelines and workloads
- Write clean, maintainable code, and perform peer code-reviews
- Write clear and concise documentation and engage in cross-team communication and knowledge sharing
- Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility
- Pair with adjacent teams to understand how your frameworks and infrastructure are actually used in the field, continuously improving them and leveraging recent advances to improve developer velocity
Requirements
- At least 5+ years of experience in Platform Engineering, DevOps, or Site Reliability Engineering (SRE).
- B.S. or M.S. degree (or equivalent) in Computer Science, Engineering, or a related field
- Proficiency in at least one modern programming languages (Python, Javascript, C#, Go, etc)
- Demonstrated industry best-practices in MLOps
- Proficiency with CI/CD tools and GitOps workflows
- Familiarity with running GPU workloads in kubernetes
- Strong knowledge of Kubernetes (self-hosted and managed) and modern k8s paradigms (e.g. CNCF)
- Proficiency with Infrastructure as Code tools (Terraform, etc) and configuration management tools (Ansible, etc)
- Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry)
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