Senior Machine Learning Systems Engineer

8 hours ago

Lucknow, Uttar Pradesh, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Description

As a Senior Machine Learning Systems Engineer, you will be responsible for designing and developing scalable machine learning systems that meet the highest standards of resilience and performance. Your primary goal is to ensure that our production services operate smoothly, with clear Service Level Objectives (SLOs), runbooks, and fast, safe rollbacks.

Your responsibilities will include:

  1. Own the process of productionizing models to guarantee resilient services.
  2. Built automation-first delivery through reproducible builds, layered tests, and environment promotion via GitLab CI and Terraform-based Infrastructure as Code.
  3. Engineered scalable serving using batch and real-time inference on EKS/ECS/Lambda and Databricks Model Serving with probes, autoscaling, and canary/blue-green deployments.
  4. Instrumented end-to-end observability to detect drift/regressions and led incidents and post-mortems that drive durable fixes.
  5. Partnered across teams to translate requirements into designs, Architectural Decision Records (ADRs), and change plans, balancing security, privacy, cost, and performance tradeoffs.
  6. Continuously reduced toil through automation and optimized model/GPU/LLM cost.

Requirements and Qualifications:

  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience.
  • 3+ years operating ML systems in production (MLOps).
  • Experience with Python for ML engineering, packaging, typing, testing, and performance.
  • Experience developing GitLab CI for ML/GenAI and Terraform for ML/GenAI.
  • Experience deploying and operating compute for ML and secure data access patterns.
  • Experience implementing MLflow tracking, model registry & governed promotion, packaging & deployment to multi-target runtimes.
  • Experience operating real-time + batch/streaming inference workloads and ML observability.
Preferred Qualifications:
  • Advanced GitLab CI and Terraform.
  • Advanced real-time serving and SLO-driven rollback/automation.
  • Databricks governance and feature platform approval/reuse workflows.

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