Senior MLOps Engineer

1 week ago

Bengaluru Chennai Hyderabad, India Ascendion Engineering Full time ₹ 75,00,000 - ₹ 1,50,00,000 per year

Job Title: Senior MLOps Engineer

Experience: 5 10 Years

Location: [Bangalore/Hydrabad/Chennai]

Employment Type: Full-time

About the Role

We are looking for an experienced MLOps Engineer to join our Data Science & AI Engineering team. The ideal candidate will bridge the gap between machine learning model development and production deployment, ensuring scalable, reliable, and automated ML pipelines. You will work closely with data scientists, data engineers, and software engineers to operationalize machine learning solutions and optimize model lifecycle management.

Key Responsibilities

  • Model Deployment & Automation:

  • Design, build, and maintain CI/CD pipelines for ML model training, validation, and deployment.

  • Automate the end-to-end ML lifecycle from data ingestion to model monitoring and retraining.

  • Infrastructure & Scalability:

  • Deploy and manage ML workloads on cloud platforms (AWS / Azure / GCP).

  • Implement scalable infrastructure using Kubernetes, Docker, and Terraform.

  • Optimize compute resources for training and inference workloads.

  • Monitoring & Governance:

  • Implement model monitoring (drift detection, performance tracking, and versioning).

  • Manage model governance, reproducibility, and compliance requirements.

  • Ensure observability across pipelines using tools like Prometheus, Grafana, or ELK stack.

  • Collaboration & Process Improvement:

  • Work with data scientists to productionize and containerize models.

  • Partner with software and DevOps teams to integrate ML systems into broader products.
  • Continuously evaluate and improve MLOps frameworks, tools, and best practices.

Required Skills and Qualifications

  • Technical Expertise:

  • Strong programming skills in Python (preferred), Go, or Java.

  • Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn.
  • Proficient in MLOps tools such as MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML.
  • Strong knowledge of Docker, Kubernetes, and CI/CD systems (Jenkins, GitHub Actions, Argo CD, etc.).

  • Solid understanding of cloud infrastructure (AWS/GCP/Azure) and infrastructure-as-code tools (Terraform, CloudFormation).

  • Data & Model Management:

  • Familiarity with feature stores, data versioning tools (DVC, Delta Lake, etc.), and model registries.

  • Experience implementing monitoring and logging for ML models in production.

  • Soft Skills:

  • Strong problem-solving, debugging, and analytical skills.

  • Excellent communication and cross-functional collaboration abilities.
  • Ability to mentor junior engineers and establish best practices.

Preferred Qualifications

  • Experience with large-scale distributed systems or real-time model serving.
  • Exposure to MLOps security, compliance, and data governance frameworks.
  • Knowledge of A/B testing, online learning, or reinforcement learning systems.
  • Contributions to open-source MLOps or DevOps projects.

Education

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
  • Certification in Cloud (AWS, GCP, or Azure) or MLOps is a plus.

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