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2 days ago
We are seeking an experienced Senior MLOps Engineer to join our team. As a key member of the organization, you will be responsible for developing and implementing efficient model deployment strategies that ensure resilient services with clear SLOs.
The ideal candidate will have a strong background in machine learning engineering, experience with Python, and proficiency in GitLab CI and Terraform-based infrastructure as code.
- Key Responsibilities:
- Automate model delivery through reproducible builds and environment promotion using GitLab CI and Terraform-based IaC.
- Design scalable serving architectures for batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.
- Instrument end-to-end observability (data, model, system); detect drift/regressions; lead incidents and post-mortems that drive durable fixes.
- Collaborate across teams to translate requirements into designs, ADRs, and change plans; balance 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.
- 3+ years operating ML systems in production (MLOps).
- Experience with Python for ML engineering (packaging, typing, testing, performance).
- Experience developing GitLab CI for ML/GenAI (multi-stage pipelines, artifacts, evaluation/security gates) and Terraform for ML/GenAI (reusable modules, drift detection); secure packaging & containerization.
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