Chief Machine Learning Operations Specialist

5 days ago

Amrāvati, Maharashtra, India beBeeMLOps Full time ₹ 2,50,00,000 - ₹ 3,00,00,000

About Us

We are seeking a Senior MLOps Engineer to lead the end-to-end design, implementation, and scaling of AI infrastructure.

Key Responsibilities:

  • Design and implement scalable ML pipelines (training, evaluation, deployment) for LLMs, CV, and multimodal models.
  • Lead efforts in model serving, versioning, automated CI/CD, and real-time monitoring of AI workflows.
  • Build and optimize GPU-backed serving infrastructure targeting p99 latency < 100 ms, 99.9% uptime, and > 80% GPU utilization.
  • Drive 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 build agentic workflows using LangChain or similar frameworks.
  • Architect RBAC-driven, isolated ML services to securely serve 100–500+ 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 SLAs/SLOs, optimize cloud spend by ≥ 20% year-over-year, and ensure GPU clusters operate at > 80% utilization.
  • Partner with AI researchers, product managers, and legal to align MLOps standards with compliance and roadmap goals.
  • Mentor junior engineers, run quarterly brown-bags, own onboarding docs (upskill 5+ engineers/quarter), and publish ≥ 1 open-source contribution or talk annually.

Required Skills and Qualifications

  • Expertise in designing and implementing scalable ML pipelines.
  • Proficiency in model serving, versioning, automated CI/CD, and real-time monitoring.
  • Experience with GPU-backed serving infrastructure optimization.
  • Knowledge of model governance, automated drift detection, and data-management best practices.
  • Familiarity with vector databases, agentic workflows, and RBAC-driven, isolated ML services.
  • Understanding of Prometheus/Grafana dashboards, ELK/Fluentd logging pipelines, and alerting.
  • Ability to maintain CI/CD pipelines for Python and TypeScript inference services.
  • Skill in defining and tracking SLAs/SLOs, optimizing cloud spend, and ensuring GPU cluster utilization.
  • Collaborative mindset with AI researchers, product managers, and legal teams.
  • Strong mentoring and leadership skills.

Benefits

  • Competitive salary and benefits package.
  • Opportunity to work with cutting-edge technology and innovation.
  • Collaborative and dynamic work environment.
  • Professional growth and development opportunities.
  • Flexible working hours and remote work options.

Others

  • The ideal candidate will have experience in leading MLOps projects and driving business outcomes.
  • A bachelor's degree in Computer Science, Mathematics, or related field is required.
  • Relevant certifications or advanced degrees are a plus.

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