4 Mlops Engineer Jobs

About Position: We are conducting an in-person hiring drive for the position of Mlops Engineer in Pune & Bengaluru on 23rd August 2025. Interview Location is mentioned below: Pune - Persistent Systems, Aryabhata-Pingala, 9A/12, Kashibai Khilare Marg, Erandawana, Pune 411004. Bangalore - Persistent Systems, The Cube at Karle Town Center Rd, DadaMastan Layout, Manayata Tech Park, Nagavara, Bengaluru, Karnataka 560024. We are looking for an experienced and talented Mlops Developer to join our growing data competency team. The ideal candidate will have a strong background in working with ML model deployment pipelines (CI/CD for ML)You will work closely with our data analysts, engineers, and business teams to ensure optimal performance, scalability, and availability of our data pipelines and analytics. Role: Mlops Engineer Job Location: All Persistent Locations Experience: 6+ Years Job Type: Full Time Employment What You'll Do: Design, build, and manage scalable ML model deployment pipelines (CI/CD for ML). Automate model training, validation, monitoring, and retraining workflows. Implement model governance, versioning, and reproducibility best practices. Collaborate with data scientists, engineers, and product teams to operationalize ML solutions. Ensure robust monitoring and performance tuning of deployed models. Expertise You'll Bring: Strong experience with MLOps tools & frameworks (MLflow, Kubeflow, SageMaker, Vertex AI, etc.). Proficient in containerization (Docker, Kubernetes). Good knowledge of cloud platforms (AWS, Azure, or GCP). Expertise in Python and familiarity with ML libraries (TensorFlow, PyTorch, scikit-learn). Solid understanding of CI/CD, infrastructure as code, and automation tools. Benefits: Competitive salary and benefits package Culture focused on talent development with quarterly promotion cycles 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 Inclusive 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 offer hybrid work options and flexible working hours to accommodate various needs and preferences. Our office is equipped with accessible facilities, including adjustable workstations, ergonomic chairs, 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. We are committed to creating an inclusive environment where all employees can thrive. Our company fosters a values-driven and people-centric work environment that enables our employees to: Accelerate growth, both professionally and personally Impact the world in powerful, positive ways, using the latest technologies Enjoy collaborative innovation, with diversity and work-life wellbeing at the core Unlock global opportunities to work and learn with the industry's best Let's unleash your full potential at Persistent "Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind."

Location- PAN India Grade- C1 to C2 Exp- 6 to 12 Years Key Responsibilities: 1. Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment 2. Collaborate with data scientists and software engineers to operationalize ML models 3. Develop and maintain CI/CD pipelines for ML workflows 4. Implement monitoring and logging solutions for ML models 5. Optimize ML infrastructure for performance, scalability, and cost-efficiency 6. Ensure compliance with data privacy and security regulations Required Skills and Qualifications: 1. Strong programming skills in Python, with experience in ML frameworks 2. Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes) 3. Proficiency in cloud platform (AWS) and their ML-specific services 4. Experience with MLOps tools 5. Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.) 6. Knowledge of data versioning and model versioning techniques 7. Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) 8. Knowledge of distributed training techniques 9. Experience with ML model serving frameworks (TensorFlow Serving, TorchServe) 10. Understanding of ML-specific testing and validation techniques

Years of Experience : 10+ Years Role : MLOps Engineer Location : Bangalore Summary We're seeking an experienced MLOps Engineer to build and maintain our computer vision infrastructure on AWS. The ideal candidate will develop model training pipeline, a comprehensive image data lake with advanced search capabilities, implement active learning pipelines for efficient annotation, and create frameworks enabling customers to deploy their own deep learning models. This role combines MLOps expertise with data engineering to create scalable, production-ready computer vision systems. Responsibilities: • Design and implement end-to-end computer vision ML training pipelines on AWS SageMaker for model training, validation, deployment, and monitoring • Architect and build a scalable image data lake solution enabling multi-modal search capabilities (structured metadata, image-to-image, text-to-image) along with data upload capability from edge devices • Develop vector embedding pipelines for visual content using AWS services and deep learning frameworks • Create APIs for seamless integration with third-party annotation services and automated dataset creation • Implement active learning pipelines that intelligently select high-value images for annotation, optimizing annotation ROI • Build data quality and validation frameworks to ensure consistency across the annotation lifecycle • Develop infrastructure automation using AWS CloudFormation/CDK for scalable deep learning workflows • Establish monitoring systems for data drift, annotation quality, and model performance • Create skeleton frameworks and templates enabling customers to deploy their own deep learning models • Optimize storage and retrieval mechanisms for large-scale image repositories Requirements: • Bachelor's or Master's degree in Computer Science, Engineering, or related field • 10+ years of experience in MLOps or ML Engineering with focus on computer vision applications • Experience building data lakes or large-scale data repositories for unstructured data • Strong understanding of vector databases, embedding models, and similarity search algorithms • Hands-on experience with AWS services (S3, SageMaker, Lambda, Step Functions, Glue) • Proficiency in Python and experience with PyTorch or TensorFlow • Experience implementing active learning systems for optimizing annotation workflows • Knowledge of RESTful API design and integration with third-party services • Familiarity with annotation tools and workflows for computer vision datasets • Experience with containerization (Docker) and orchestration (Kubernetes/EKS) • Understanding of data governance and security best practices for sensitive image data

Develop and deploy ML pipelines using MLOps tools, build FastAPI-based APIs, support LLMOps and real-time inferencing, collaborate with DS/DevOps teams, ensure performance and CI/CD compliance in AI infrastructure projects. Required Candidate profile Experienced Python developer with 4–8 years in MLOps, FastAPI, and AI/ML system deployment. Exposure to LLMOps, GenAI models, containerized environments, and strong collaboration across ML lifecycle