MLOps / LLMOps Engineer (Mid-Level)

Cornerstone Global Partners (CGP Group); India; A distancia; INR 1.800.000 - 3.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Competitive compensation

Descripción de la vacante

Cornerstone Global Partners (CGP Group) is seeking an experienced MLOps/LLMOps Engineer to join our AI/ML team. The role focuses on getting models from development to production, serving endpoints, and maintaining reliability with monitoring and alerts in a Databricks-heavy, Azure-centric environment with some AWS.

You will implement CI/CD for ML/LLM assets, manage data contracts, security controls, and SLO-based instrumentation.

Formación

• 3 to 5 years of experience in MLOps, LLMOps, ML Engineering, or platform-focused ML engineering.
• Hands-on experience deploying, serving, and monitoring ML models in production.
• Hands-on LLMOps experience with LLMs or foundation models in production.
• Hands-on Databricks experience (Jobs and Workflows, Delta Lake, Unity Catalog, SQL Warehouses).
• Hands-on experience with Azure and AWS.
• CI/CD experience with GitHub Actions and Databricks Asset Bundles.
• Strong Python and SQL.
• Security-first mindset (RBAC/ABAC, PII handling, data-access controls).
• Based in India and legally authorized to work in India.

Responsabilidades

• Ship ML models to production, serve them as endpoints, and maintain and monitor them.
• Detect performance drift, data drift, and other model issues, and alert the right teams.
• Operate LLMs and foundation models in production, including RAG pipelines and vector search.
• Operationalize the ML lifecycle on Databricks using Delta Lake and Unity Catalog.
• Build CI/CD for ML/LLM assets with GitHub Actions and Databricks Asset Bundles across DEV, QA, and PROD.
• Integrate data contracts, quality gates, and automated validation into ML/LLM pipelines.
• Apply security and governance controls, including PII masking and data residency policies.
• Instrument pipelines against defined SLOs, with dashboards, alerting, and runbooks.
• Monitor and optimize compute, serving, and LLM/API costs.

Conocimientos

Python

SQL

Herramientas

Databricks

Azure

AWS

GitHub Actions

Databricks Asset Bundles

Descripción del empleo

About Our Client

Our client is a growing SaaS company that provides cloud-based software to help energy, utility, telecom, and infrastructure companies protect their critical network infrastructure, and is expanding its platform with new data-driven and AI-powered capabilities.

Remote - India

About Our Client

Our client is a growing SaaS company that provides cloud-based software to help energy, utility, telecom, and infrastructure companies protect their critical network infrastructure, and is expanding its platform with new data-driven and AI-powered capabilities.

About The Role

We are looking for an MLOps / LLMOps Engineer to join the AI/ML team. This role focuses on the operations side of machine learning: once a model is built, you will help data scientists and the infrastructure team ship it to production, serve it as an endpoint, and keep it reliable through monitoring and alerting. You will also run the operations of LLMs and foundation models in production as the team builds more GenAI use cases. The environment is Databricks-heavy, running on Azure with some AWS.

Key Responsibilities

• Ship ML models to production, serve them as endpoints, and maintain and monitor them.
• Detect performance drift, data drift, and other model issues, and alert the right teams.
• Operate LLMs and foundation models in production, including RAG pipelines and vector search.
• Operationalize the ML lifecycle on Databricks using Delta Lake and Unity Catalog.
• Build CI/CD for ML/LLM assets with GitHub Actions and Databricks Asset Bundles across DEV, QA, and PROD.
• Integrate data contracts, quality gates, and automated validation into ML/LLM pipelines.
• Apply security and governance controls, including PII masking and data residency policies.
• Instrument pipelines against defined SLOs, with dashboards, alerting, and runbooks.
• Monitor and optimize compute, serving, and LLM/API costs.

Requirements

• 3 to 5 years of experience in MLOps, LLMOps, ML Engineering, or platform-focused ML engineering.
• Strong, hands-on experience deploying, serving, and monitoring ML models in production.
• Hands-on LLMOps experience with LLMs or foundation models in production.
• Hands-on Databricks experience (Jobs and Workflows, Delta Lake, Unity Catalog, SQL Warehouses).
• Hands-on experience with Azure and AWS.
• CI/CD experience with GitHub Actions and Databricks Asset Bundles.
• Strong Python and SQL.
• Security-first mindset (RBAC/ABAC, PII handling, data-access controls).
• Based in India and legally authorized to work in India.

Nice-to-Have

• Oil & gas, pipeline, utility, or infrastructure industry experience.
• RAG, LLM evaluation frameworks, and AI guardrails.
• Geospatial data experience (PostGIS, spatial joins).
• Power BI with Databricks SQL Warehouses.
• FinOps and Databricks disaster-recovery practices.

What We Offer

• Be part of a dynamic and growing company that is well-respected in its industry.
• Competitive compensation based on experience and qualifications.
• Health insurance coverage.

As part of our hiring process, this role may use artificial intelligence or automated tools to assist with reviewing and screening applications. These tools support, but do not replace, human judgment in making hiring decisions.