Lead MLOps Engineer

3 weeks ago


Mumbai, India Zyoin Group Full time

Position : Lead MLOps : 9+ : Mumbai, the Role :We are looking for a Lead MLOps Engineer who will lead and support the end-to-end deployment, monitoring, and optimization of machine learning and data-driven applications across cloud platforms. You will collaborate with data scientists, engineers, and business stakeholders to ensure scalable, secure, and highly available ML Responsibilities :- Be a hands-on contributor capable of independently designing and developing complete MLOps solutions from scratch.- Lead end-to-end ML pipeline development, deployment, and monitoring across GCP and Azure.- Build and maintain CI/CD pipelines using tools like ArgoCD, Git, and Docker.- Automate and optimize ML model training, validation, deployment, and scaling using Kubernetes, Kubeflow, or similar orchestration platforms.- Develop data processing workflows using Python and PySpark on distributed systems.- Implement observability using tools like Grafana, NewRelic, and cloud-native monitoring solutions.- Collaborate with Data Scientists to transition research into production-grade solutions.- Guide and mentor junior engineers, enforce coding standards, and conduct code reviews.- Demonstrate business understanding to align ML pipelines with product goals.- Manage infrastructure as code (IaC) for reproducibility and scalability.- Exposure to AI and RAG-related development, various GPU and AI Platforms Skills & Experience :- 9+ years of hands-on experience in MLOps roles.- Strong proficiency in Python and PySpark with clean and scalable code practices.- Expertise in GCP and Azure cloud platforms including compute, storage, and networking components.- Proven experience in deploying and managing containerized applications using Docker and Kubernetes.- Hands-on with CI/CD tools preferably ArgoCD, GitHub Actions, or GitLab CI.- Experience in monitoring, logging, and alerting using tools such as Grafana, NewRelic, Prometheus, or similar.- Understanding of ML model lifecycle, versioning, and performance monitoring.- Experience with MLFlow for model versioning.- Ability to create REST APIs using FastAPI, Flask, or Django.- Strong problem-solving, communication, and stakeholder management skills.- Experience mentoring teams and driving end-to-end project execution.- Exposure to Vertex AI Pipeline in GCP or similar in other clouds is a plus. (ref:hirist.tech)


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