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MLOps Engineer

MLOps Engineer

Persistent

5 - 8 years

27 - 37 Lacs

pune

Posted:1 day ago| Platform:

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Skills Required

ci/cd automation kubernetes sagemaker azure ml docker vertex ai cloud ml platforms

Work Mode

Work from Office

Job Type

Full Time

Job Description

About Position:

We are hiring a skilled MLOps Engineer to build and manage robust ML pipelines that support scalable, secure, and automated deployment of machine learning models. This role is critical in enabling seamless collaboration between data science, engineering, and DevOps teams for enterprise-grade AI/ML adoption.

Role: MLOps Engineer
Location: All Persistent Location
Experience: 5 to 8 years
Job Type: Full Time Employment

What You'll Do:

You will design and automate ML pipelines, deploy models at scale, and ensure operational excellence across AI/ML systems.
Build and manage end-to-end MLOps pipelines for model training, testing, deployment, monitoring, and retraining
Implement CI/CD workflows for ML models using Jenkins, GitHub Actions, or ArgoCD
Automate model deployment using Docker, Kubernetes, and Kubeflow
Collaborate with data scientists and ML engineers to productionize models and ensure reproducibility
Monitor model performance and data drift, enabling timely retraining and updates
Manage model versioning, lineage, and governance
Integrate ML workflows with cloud platforms (GCP Vertex AI, AWS SageMaker, Azure ML)
Implement logging, monitoring, and alerting systems for deployed ML services
Optimize ML workloads for scalability, efficiency, and cost-effectiveness
Ensure adherence to security, compliance, and responsible AI practices in MLOps

Expertise You'll Bring:

Youll bring hands-on experience in MLOps engineering, cloud-native platforms, and automation tools, with a strong focus on reliability and scalability.
58 years of IT/DevOps/Data Engineering experience, with at least 3+ years in MLOps
Strong programming skills in Python (experience with ML/AI libraries is a plus)
Hands-on with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, ArgoCD)
Proficiency in containerization & orchestration (Docker, Kubernetes)
Experience with MLOps tools: MLflow, Kubeflow, Airflow, TFX
Familiarity with cloud ML services (Vertex AI, SageMaker, Azure ML)
Knowledge of model monitoring frameworks (Prometheus, Grafana, Evidently AI)
Strong background in version control (Git) and artifact management
Understanding of Agile/Scrum delivery practices

Benefits:

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
Annual health check-ups
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 Ltd. 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

Let's unleash your full potential at Persistent - persistent.com/careers

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

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MLOps Engineer