Senior Machine Learning Operations Engineer
2 weeks ago
In this pivotal role, you will be responsible for ensuring the smooth operation of our machine learning models and services.
Key Responsibilities:- Model Productionization: Develop and execute a strategy for taking tracked experiments to production, incorporating clear Service Level Objectives (SLOs), runbooks, and fast, safe rollbacks.
- Automation-First Delivery: Build reproducible builds, layered tests, and environment promotion using GitLab CI and Terraform-based Infrastructure as Code (IaC).
- Scalable Serving: Engineer batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving, with probes, autoscaling, and canary/blue-green deployments.
- Observability and Incident Management: Instrument end-to-end observability, detect drift/regressions, and lead incidents and post-mortems to drive durable fixes.
- Collaboration and Partnership: Partner across teams to translate requirements into designs, Architecture Decision Records (ADRs), and change plans, balancing security, privacy, cost, and performance tradeoffs.
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience; or High School Diploma/General Education Degree and 6+ years of relevant experience in lieu of Bachelor's Degree.
- 3+ years operating ML systems in production.
- Experience with Python for ML engineering, GitLab CI for ML/GenAI, and Terraform for ML/GenAI.
- Experience deploying and operating compute for ML, secure data access patterns, and implementing MLflow tracking, model registry, and governed promotion.
What We Offer:
- A dynamic work environment that fosters collaboration and innovation.
- The opportunity to work with cutting-edge technologies and contribute to high-impact projects.
- A competitive salary and benefits package.
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