This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI ML Operations Engineer based in India.

This is an opportunity to lead the engineering and operational foundations behind scalable AI and machine learning systems.
You will design reliable MLOps platforms and production pipelines that support advanced AI workloads at enterprise scale.
The role combines model deployment, cloud infrastructure, automation, observability, governance, and cost optimization.
You will work across large-scale data environments while enabling data scientists and engineers to move models efficiently into production.
The position offers exposure to modern technologies including Databricks, MLflow, RAG architectures, vector search, and AI agent frameworks.
You will also help establish secure, resilient, and measurable systems that support high-availability products and intelligent applications.
This role is ideal for an experienced MLOps professional who enjoys solving complex infrastructure challenges and driving AI innovation.

Accountabilities

Design, develop, and maintain stable, scalable, reliable, and secure AI/ML Operations platforms and production pipelines.
Package, deploy, and manage AI/ML services in production while ensuring deployments are reproducible, maintainable, and interpretable.
Build and optimize CI/CD pipelines that automate model deployment and accelerate the transition from development to production.
Provision and manage infrastructure for model training and inference using technologies such as Docker, Kubernetes, serverless platforms, and Infrastructure as Code.
Implement monitoring and observability for model performance, data drift, latency, reliability, and other production metrics.
Automate model retraining and data workflows to maintain model quality and operational consistency over time.
Manage foundation model deployments, fine-tuning workflows, and Retrieval-Augmented Generation architectures involving vector databases and knowledge graphs.
Support AI/ML workloads using platforms and technologies such as AWS Bedrock, Databricks, MLflow, Mosaic AI, Unity Catalog, and Vector Search.
Optimize GPU and CPU utilization, infrastructure architecture, and cloud resources to control costs while maintaining efficient, low-latency inference.
Establish versioning and governance practices for data, code, and machine learning models.
Implement appropriate security, privacy, and data governance controls to protect sensitive information and support compliance requirements.
Troubleshoot complex platform, data, infrastructure, and production issues while maintaining high levels of system availability and reliability.
Partner closely with data scientists, data engineers, software engineers, and other technical stakeholders to bridge model development and production operations.
Evaluate emerging AI and data technologies and identify opportunities to improve infrastructure, automation, and engineering practices.

Requirements

Proven experience building and maintaining AI/ML Operations platforms designed for scalability, reliability, efficiency, and security in enterprise environments.
Strong experience working with large-scale structured and unstructured data, including complex data platforms handling very high data volumes.
In-depth experience with the Databricks Lakehouse ecosystem and AI/ML workflows involving Databricks and MLflow.
Hands-on knowledge of Mosaic AI Agent Framework, Unity Catalog, Vector Search, and Knowledge Graph technologies.
Experience integrating AI/ML Operations pipelines with frameworks such as LangChain and LangGraph.
Strong programming skills in Python and SQL.
Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP, with AWS-based data platforms being particularly valuable.
Experience with modern software engineering and infrastructure practices, including Kubernetes, CI/CD, Infrastructure as Code, preferably Terraform, monitoring, observability, and alerting.
Experience with model deployment, retraining automation, production monitoring, data drift detection, and AI/ML system reliability.
Knowledge of foundation models, fine-tuning, Retrieval-Augmented Generation, vector databases, and AI agent architectures.
Strong understanding of cloud resource management, infrastructure optimization, and designing systems with cost efficiency in mind.
Experience supporting highly available and scalable enterprise SaaS or technology platforms.
Strong analytical, troubleshooting, communication, and problem-solving abilities.
Ability to collaborate effectively across data science, data engineering, software engineering, and infrastructure teams.
Legally authorized to work in India on an ongoing basis.

Benefits

Opportunity to work on advanced AI and machine learning infrastructure at enterprise scale.
Exposure to modern technologies across MLOps, Databricks, generative AI, cloud platforms, and AI agent ecosystems.
An environment that encourages innovation, experimentation, and thoughtful technical problem-solving.
Opportunity to collaborate with experienced engineers, data scientists, and technology professionals across disciplines.
Support for professional growth and opportunities to expand expertise in emerging AI and data technologies.
Inclusive environment that values diverse perspectives, continuous learning, and meaningful technical contributions.
Opportunity to contribute to scalable products and platforms while working with modern engineering practices.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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