DevOps Engineer with ML Ops

1 month ago

Gurugram, India TrueFan Full time

Job Description: We are seeking an experienced DevOps Engineer with a strong background in MLOps to join our growing team. You will be responsible for designing, implementing, and maintaining the infrastructure and tools that enable seamless integration of Machine Learning (ML) models into production environments. The ideal candidate has deep knowledge in both traditional DevOps practices and MLOps, with hands-on experience in deploying, monitoring, and managing ML workflows at scale. Must have knowledge on Kubernetes, Docker, Jenkins and large models deployment from 10 - 200 GBs. Read to work in multiple cloud environments and utmost focus on cost of the cloud. Must be able to do 24*7 monitoring of the services and cost associated with it. 

Key Responsibilities:


  • Design, implement, and maintain CI/CD pipelines for both traditional software applications and Machine Learning models.
  • Automate ML workflows, including model training, validation, deployment, and monitoring. 
  • Familiarity with large models deployment upto 200gb and best way to deploy them in an autoscale way using kubernetes
  • Collaborate with data scientists and software engineers to deploy scalable ML models in production environments.
  • Containerize machine learning models and applications using Docker, Kubernetes
  • Manage and monitor cloud-based infrastructure (AWS, GCP, Azure, E2E) to ensure efficient resource utilization for ML workloads.
  • Ensure high availability, fault tolerance, and scalability of ML systems and pipelines.
  • Monitor model performance in production, implement model retraining pipelines, and ensure continuous improvement.
  • Ensure security and compliance best practices in DevOps and MLOps processes.
  • Troubleshoot and resolve any issues related to ML infrastructure, pipeline execution, and production deployments.

Required Qualifications:


  • 2-3 years of experience in DevOps, with a focus on ML Ops being a plus.
  • Experience with cloud platforms (AWS, GCP, E2E or Azure)
  • Proficient in CI/CD tools like Jenkins, GitLab CI, CircleCI, or similar.
  • Strong expertise in containerization technologies (Docker, Kubernetes).
  • Good to have experience with ML frameworks and libraries ( PyTorch).
  • Knowledge of version control systems like Git, GitHub, GitLab.
  • Programming skills in Python, Bash, or similar scripting languages.
  • Knowledge of monitoring and logging tools (Prometheus, Grafana, ELK Stack) and model monitoring tools.
  • Understanding of ML lifecycle, including model development, experimentation, versioning, and deployment.

Preferred Qualifications:


  • Experience with security best practices in DevOps and MLOps pipelines.
  • Understanding of model explainability and bias mitigation techniques.

Soft Skills:


  • Excellent problem-solving and analytical skills.
  • Strong collaboration and communication skills for working with cross-functional teams.
  • Ability to work in fast-paced environments and handle multiple priorities.
  • Continuous learner with a growth mindset, always looking for opportunities to improve processes and systems.

What We Offer:


  • Competitive salary and benefits.
  • Opportunity to work with cutting-edge ML and DevOps technologies.
  • Work in a dynamic and innovative environment with a talented team.
  • Career growth and development opportunities.


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