Senior AI Engineering Lead

1 week ago

Agra, Uttar Pradesh, India beBeeMloper Full time ₹ 15,00,000 - ₹ 30,00,000
Lead AI Infrastructure Developer

Our organization is seeking a senior expert in MLOps to oversee the design, development, and scaling of our artificial intelligence infrastructure. This role demands close collaboration with researchers, product teams, and DevOps professionals to transform prototypes into production-ready services that meet stringent performance standards for latency, reliability, and cost efficiency.

Key Responsibilities:

  • Develop and implement scalable machine learning pipelines (training, evaluation, deployment) for large language models, computer vision, and multimodal models.
  • Drive efforts in model serving, versioning, automated continuous integration/continuous deployment, and real-time monitoring of AI workflows.
  • Design and optimize GPU-backed serving infrastructure targeting p99 latency < 100 ms, 99.9% uptime, and > 80% GPU utilization.
  • Initiate initiatives on model governance, automated drift detection (≤10% false positives), and data-management best practices.
  • Integrate vector databases (Qdrant, Pinecone) for low-latency semantic retrieval, and develop agent-based workflows using LangChain or similar frameworks.
  • Architect RBAC-driven, isolated ML services to securely serve multiple organizations.
  • Design Prometheus/Grafana dashboards, ELK/Fluentd logging pipelines, and alerting for all ML workloads.
  • Maintain CI/CD pipelines for Python (FastAPI) and TypeScript (NestJS) inference services.
  • Define and track service level agreements/service level objectives, optimize cloud expenses by ≥ 20% year-over-year, and ensure GPU clusters operate at > 80% utilization.
  • Collaborate with AI researchers, product managers, and legal teams to align MLOps standards with compliance and roadmap goals.
  • Coach junior engineers, conduct quarterly knowledge-sharing sessions, own documentation (upskill 5+ engineers/quarter), and publish ≥ 1 open-source contribution or talk annually.

Required Skills and Qualifications:

  • Minimum 4 years of experience in MLOps or ML infrastructure, preferably within software engineering.
  • Strong expertise in cloud platforms (AWS/GCP/Azure), Kubernetes, Docker, Terraform, Helm, Kubeflow, and MLflow.
  • Experience with inference frameworks (Triton, TensorFlow Serving, BentoML, TorchServe).
  • Familiarity with distributed training, workload schedulers, and GPU-cluster orchestration.
  • Proficiency in Python, TypeScript, and infrastructure-as-code (Terraform, Helm, etc.).
  • A proven track record of building reliable, scalable ML systems in production environments.

Benefits:

  • A competitive salary package.
  • A comprehensive benefits plan, including health insurance, retirement savings, and paid time off.
  • Opportunities for professional growth and development.
  • A dynamic and supportive work environment.

Other Opportunities:

Apply now if you are a motivated and experienced MLOps engineer seeking a challenging role. We look forward to hearing from you

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