Senior MLOps Engineer

Unico Connect LLP.; Mumbai; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

Unico Connect LLP. is looking for a Senior MLOps Engineer to architect and operate the ML platform powering AI delivery across client engagements. The role includes designing deployment patterns and monitoring solutions, while leading model deployment on multiple cloud platforms.

The ideal candidate will have over 5 years in MLOps platform engineering, with deep cloud expertise. This position is well-suited for engineers who have hands-on Kubernetes knowledge and a proven track record in mentoring.

Qualifications

• 5+ years of MLOps or platform engineering with at least 1 production ML or LLM platform shipped.
• Deep cloud experience on GCP, AWS, or both at production scale.
• Strong Python; comfortable working through PyTorch, TensorFlow, or JAX internals.
• Kubernetes production experience including operators (Kubeflow, Argo).
• Hands-on with model serving (Triton, vLLM, TGI, KServe, or Ray Serve).
• Strong fundamentals in observability (Prometheus, Grafana, OpenTelemetry).
• Track record of mentoring junior MLOps and DevOps engineers.
• Excellent written communication for design documents and platform retrospectives.

Responsibilities

• Architect the ML platform: training pipelines, model registry, feature store, deployment, and monitoring.
• Design LLM ops infrastructure: prompt versioning, evaluation pipelines, cost dashboards, and fallback routing.
• Lead model deployment on GCP Vertex AI, AWS Bedrock and SageMaker, or self-hosted platforms.
• Mentor 1-2 MLOps Engineers; set MLOps standards and review pull requests against them.
• Drive cost optimisation through model tiering, caching strategies, batch inference.
• Govern compliance posture for ML platform components including SOC 2, HIPAA, and GDPR requirements.

Skills

MLOps or platform engineering

Cloud experience (GCP, AWS)

Python

Kubernetes

Model serving (Triton, vLLM, TGI, KServe)

Observability tools (Prometheus, Grafana)

Mentoring

Cost-optimisation

Communication

Education

Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Job description

Unico Connect is seeking a Senior MLOps Engineer to architect and operate the ML platform that powers AI delivery across client engagements. The role designs deployment patterns, observability stacks, and the AI-engineering platform that takes models from proof of concept to enterprise production. The position is well suited to senior platform engineers with deep cloud experience, hands-on Kubernetes expertise, and a track record of building developer-productivity wins for ML teams.

Responsibilities

• Architect the ML platform: training pipelines, model registry, feature store, deployment, and monitoring
• Design LLM ops infrastructure: prompt versioning, evaluation pipelines, cost dashboards, and fallback routing
• Lead model deployment on GCP Vertex AI, AWS Bedrock and SageMaker, or self-hosted platforms (Modal, Ray Serve, vLLM)
• Mentor 1-2 MLOps Engineers; set MLOps standards and review pull requests against them
• Drive cost optimisation through model tiering, caching strategies, batch inference, and spot instance usage
• Partner with AI Engineers and the Tech Lead on production-readiness reviews
• Govern compliance posture for ML platform components including SOC 2, HIPAA, and GDPR requirements
• Lead capacity planning for GPU and inference workloads
• Design rollback, canary, and shadow-traffic patterns for risky model deployments
• Author internal MLOps playbooks covering incident response, drift remediation, and cost emergencies
• Run quarterly platform retrospectives and roadmap reviews

Qualifications

• 5+ years of MLOps or platform engineering with at least 1 production ML or LLM platform shipped
• Deep cloud experience on GCP, AWS, or both at production scale
• Strong Python; comfortable working through PyTorch, TensorFlow, or JAX internals
• Kubernetes production experience including operators (Kubeflow, Argo)
• Hands-on with model serving (Triton, vLLM, TGI, KServe, or Ray Serve)
• Strong fundamentals in observability (Prometheus, Grafana, OpenTelemetry)
• Track record of mentoring junior MLOps and DevOps engineers
• Capacity to lead cost-optimisation initiatives at six-figure annual cloud spend
• Excellent written communication for design documents and platform retrospectives
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field