Machine Learning Operations Site Reliability Engineer

Persistent Systems Limited; Bengaluru; Hybrid; INR 1,800,000 - 2,400,000; Full time

Benefits offered by this job

Hybrid work arrangement

Education sponsorship & growth

Healthcare & life insurance

Job summary

Persistent Systems Limited is seeking a Machine Learning Operations Site Reliability Engineer to design and manage MLOps and LLMOps platforms supporting the full ML lifecycle.

You will collaborate with data scientists and platform teams to ensure secure, scalable, and observable AI deployments, including automation of infrastructure, CI/CD, and governance practices. A hybrid work setup and ongoing learning opportunities are offered.

Qualifications

• 5-8 years of experience in ML Ops, SRE, DevOps or related fields.
• Hands-on with ML lifecycle management and deployment pipelines.
• Experience with LLM deployment and GenAI applications preferred.
• Strong knowledge of observability, security, and governance for AI platforms.

Responsibilities

• Design, implement, and maintain MLOps/LLMOps pipelines for AI workloads.
• Build scalable model development, testing, deployment, and monitoring frameworks.
• Operationalize ML models and LLM-based apps in production environments.
• Develop Agentic AI and RAG-based applications in production.
• Implement CI/CD and Continuous Training pipelines for ML models.

Skills

MLOps

Python

CI/CD

Observability

LLMOps

Automation

Security & Compliance

Cloud platforms

Education

Bachelor's degree in CS/related field

Tools

Docker

Kubernetes

AWS

Terraform

Job description

Machine Learning Operations Site Reliability Engineer

Job Description

About Persistent

We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what’s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.

We are seeking a skilled Machine Learning Operations Site Reliability Engineer (SRE) to join our growing AI and Engineering team. In this role, you will be responsible for designing, implementing, and managing robust MLOps and LLMOps platforms that support the complete machine learning lifecycle, from model development to production deployment, monitoring, and optimization.

• Role: Machine Learning Operations Site Reliability Engineer
• Experience: 5 to 8 Years
• Job Type: Full-Time Employment

What You'll Do:

• Design, implement, and maintain enterprise-grade MLOps and LLMOps pipelines for AI and machine learning workloads.
• Build secure, scalable, and reproducible model development, testing, deployment, and monitoring frameworks.
• Support the operationalization of machine learning models and Large Language Model (LLM)-based applications.
• Develop and manage Agentic AI and Retrieval-Augmented Generation (RAG) applications in production environments.
• Implement CI/CD and CT (Continuous Training) pipelines for machine learning models and AI solutions.
• Establish observability frameworks for monitoring model accuracy, latency, drift, performance, availability, and reliability.
• Conduct model benchmarking, load testing, and performance optimization activities.
• Implement security controls, governance standards, and compliance requirements across AI platforms.
• Automate infrastructure provisioning, deployment, monitoring, and operational workflows.
• Support application lifecycle management across development, testing, staging, and production environments.
• Monitor platform health and proactively identify potential risks, bottlenecks, and reliability issues.
• Troubleshoot production incidents and participate in root cause analysis activities.
• Create and maintain technical documentation, architecture guidelines, operational runbooks, code samples, and implementation blueprints.
• Collaborate with Data Scientists, ML Engineers, Security Teams, and Platform Architects to deliver reliable AI solutions.
• Drive platform improvements focused on scalability, resiliency, operational efficiency, and automation.
• Implement best practices for model lifecycle management, versioning, governance, and auditability.

Expertise You'll Bring:

• 5-8 years of experience in Machine Learning Operations, Site Reliability Engineering, DevOps, Platform Engineering, or related domains.
• Strong hands-on experience with MLOps and Machine Learning lifecycle management.
• Experience designing and implementing scalable AI/ML deployment pipelines.
• Strong understanding of LLMOps concepts and deployment of Generative AI applications.
• Experience supporting production AI/ML platforms and mission-critical workloads.
• Knowledge of model versioning, experiment tracking, model registry, and governance frameworks.
• Experience implementing observability, logging, monitoring, tracing, and alerting solutions for AI applications.
• Strong understanding of security, compliance, and responsible AI practices.
• Experience with performance benchmarking, model evaluation, and optimization techniques.
• Hands-on expertise with automation frameworks and infrastructure management.
• Strong programming experience in Python and automation scripting.
• Experience with containerization technologies such as Docker.
• Hands-on experience with Kubernetes and container orchestration platforms.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Understanding of CI/CD practices, Infrastructure as Code, and DevOps methodologies.
• Experience deploying and managing RAG-based and Agentic AI applications.
• Knowledge of multimodal AI workflows and Large Language Models.
• Strong troubleshooting, analytical, and problem-solving skills.
• Excellent communication and collaboration skills with the ability to work across cross-functional teams.
• Ability to operate effectively in fast-paced and dynamic enterprise environments.
• Competitive salary and benefits package
• Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
• Opportunity to work with cutting-edge technologies
• Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
• Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents

Values-Driven, People-Centric & Inclusive Work Environment:

Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.

• We support hybrid work and flexible hours to fit diverse lifestyles.
• Our office is accessibility-friendly, with ergonomic setups and assistive technologies to support employees with physical disabilities.
• If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment

“Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”