Turn Machine Learning into Production at Scale :

If you're passionate about building production-grade AI systems, automating ML pipelines, and deploying cutting-edge LLM & Generative AI solutions, this opportunity is for you.

We're looking for an experienced MLOps Engineer who thrives at the intersection of Machine Learning, Cloud Infrastructure, DevOps, and Generative AIsomeone who can transform innovative models into scalable, enterprise-ready solutions.

Location : Bangalore

Experience : 6 to 10 Years

Preference : Immediate / Short Notice Candidates

What You'll Own :

- Build and manage scalable, production-ready ML pipelines.

- Deploy, monitor, and optimize machine learning models across enterprise environments.

- Design robust CI/CD workflows for end-to-end ML lifecycle automation.

- Develop and operationalize LLM applications, RAG pipelines, and AI-powered solutions.

- Collaborate with Data Scientists, Cloud Engineers, and Platform Teams to accelerate AI adoption.

- Improve reliability, scalability, observability, and performance of ML infrastructure.

Technical Expertise We're Looking For :

Cloud ML Platforms :

- GCP Vertex AI

- AWS SageMaker

- Azure Machine Learning Studio

MLOps & Workflow Automation :

- Apache Airflow

- Kubeflow

Infrastructure & DevOps :

- Docker

- Kubernetes

- Terraform

Programming :

- Python

- Bash Scripting

Generative AI Stack :

- LangChain

- RAG Frameworks

- Vector Databases

- LLM Application Development

You're a Great Fit If You :

- Have 6 to 10 years of MLOps / ML Engineering experience.

- Have successfully deployed ML models into production.

- Enjoy automating infrastructure and ML workflows.

- Understand the complete ML lifecyclefrom experimentation to monitoring.

- Have hands-on experience with Generative AI, LLMs, and Retrieval-Augmented Generation (RAG).

Why This Role :

Work on enterprise-scale AI platforms where you'll build intelligent systems that power real-world business decisions. If you're excited about solving complex AI infrastructure challenges and shaping the next generation of production ML platforms, we'd love to hear from you.

Location : Bangalore (Hybrid/Onsite)