
AI/ML Expert
2 days ago
Job Title:
Senior AI/ML Engineering Lead
About the Role:
The Senior AI/ML Engineering Lead will be responsible for driving productionization of models, building automation-first delivery pipelines and engineering scalable serving solutions.
Key Responsibilities:
- Own the development and implementation of ML systems in production, ensuring resilient services with clear SLOs, runbooks and fast, safe rollbacks.
- Build automation-first delivery pipelines using GitLab CI and Terraform-based IaC, focusing on reproducible builds, layered tests and environment promotion.
- Engineer scalable serving solutions for batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving, incorporating probes, autoscaling and canary/blue-green deployments.
- Instrument end-to-end observability, detect drift/regressions and lead incidents and post-mortems to drive durable fixes.
- Partner with cross-functional teams to translate requirements into designs, ADRs and change plans, balancing security, privacy, cost and performance tradeoffs.
- Continuously reduce toil through automation, optimize model/GPU/LLM cost and evolve templates/playbooks for repeatable delivery.
Requirements:
- Bachelor's degree in Computer Science, Engineering, Data Science or a related field, and 3+ years of relevant experience as outlined in the key responsibilities; or High School Diploma/General Education Degree and 6+ years of relevant experience as outlined in the key responsibilities in lieu of Bachelor's Degree.
- 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.
- Experience deploying and operating compute for ML (EKS/ECS/Lambda), and secure data access patterns (S3/VPC/IAM/KMS, private endpoints).
- Experience implementing MLflow tracking, model registry & governed promotion, packaging & deployment to multi-target runtimes.
- Experience operating real-time + batch/streaming inference workloads, ML observability, layered testing (unit/integration), workflow orchestration and cost optimization.
- Experience designing and implementing IAM least-privilege, secrets/key management for CI/CD pipelines; privacy and compliance awareness.
Preferred Qualifications:
- Advanced GitLab CI (dynamic child pipelines, components, cross-project triggers, security scans, compliance gates).
- Advanced Terraform (policy-as-code, gated plan/apply, environment promotion).
- Advanced real-time serving (multi-tenant routing, dynamic model loading) and SLO-driven rollback/automation.
- Databricks governance (Unity Catalog, lineage) and feature platform approval/reuse workflows.
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