India
about 21 hoursMLOps / LLMOps Engineer (Mid-Level)
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.
Your application will only be counted once you complete the full registration process on the KeyStone platform, including creating your profile, uploading your CV, and submitting your application. The AI interview is optional and encouraged, but is not required for your application to be counted.
* Questions marked with an asterisk are required for eligibility.
