Highly Skilled Machine Learning Operations Specialist

19 hours ago

Aligarh, Uttar Pradesh, India beBeeMachineLearningEngineer Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Senior MLOps Engineer Job Description

This is a critical role for productionizing models from tracked experiments to governed releases, ensuring resilient services with clear SLOs, runbooks, and fast, safe rollbacks.

The ideal candidate will be responsible for building automation-first delivery, reproducible builds, layered tests, and environment promotion via GitLab CI and Terraform-based IaC.

They will also engineer scalable serving, batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.

Additionally, the candidate will instrument end-to-end observability (data, model, system), detect drift/regressions, lead incidents and post-mortems that drive durable fixes.

Partnering across teams to translate requirements into designs, ADRs, and change plans; balance security, privacy, cost, and performance tradeoffs.

Continuously reduce toil through automation, optimize model/GPU/LLM cost, and evolve templates/playbooks for repeatable delivery.

Required Skills and Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field and 3+ years of relevant experience as outlined in essential duties; or High School Diploma/General Education Degree and 6+ years of relevant experience as outlined in essential duties 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.
Benefits and Expectations

We offer a competitive compensation package and opportunities for professional growth and development.

The successful candidate will be part of a collaborative team working together to drive innovation and success.

As part of this team, you will have the opportunity to develop your skills and expertise while contributing to complex projects.

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