Senior AI ML Operations Engineer
RemoteIndia
Job Summary
Design and maintain stable, scalable AI/ML operations platforms and pipelines, managing model deployment, CI/CD automation, and infrastructure provisioning across Docker, Kubernetes, and serverless environments. Implement monitoring for data drift and latency, automate retraining workflows, and optimize GPU/CPU utilization to minimize cloud costs while ensuring low-latency inference. Collaborate with data scientists and engineers to bridge development and production, handling foundation models, fine-tuning, and RAG stacks using Vector DBs and knowledge graphs. Diagnose complex data issues, enforce security and compliance policies, and evaluate emerging technologies to improve data infrastructure. Work within the Databricks Lakehouse ecosystem, leveraging Python, SQL, and AWS to manage large-scale structured and unstructured data.
Required Qualifications
- Enterprise SaaS software solutions with high availability and scalability
- Solution handling large scale structured and unstructured data from varied data sources
- Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
- In depth experience in AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
- AI/MLOps workflows on Databricks
- MLFlow
- Mosaic AI Agent Framework
- Unity Catalog
- Vector Search
- Knowledge Graph
- Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
- Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP)
- Experience in AWS hosted data platform
- Programming languages like Python and SQL
- Modern software engineering practices like Kubernetes, CI/CD, IAC tools
- Observability, monitoring and alerting
- Solution Cost Optimisations and design to cost
- Legally eligible to work in India on an ongoing basis
Desired Qualifications
- Experience with AWS Bedrock
- Experience with Docker
- Experience with Kubernetes
- Experience with serverless platforms
- Experience in Monte Carlo
- Experience with Terraform
- Experience with LangChain
- Experience with LangGraph
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