Machine Learning Engineer

1 day ago

Mumbai, Maharashtra, India Zyoin Group Full time

Position: Lead MLOps Engineer

Experience: 9+ Years

Location: Mumbai, Mahape

Email ID for CV sharing:

About 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 systems.

Key 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 required.

Required 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.

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