MLOps Technical Lead
Technology, Data & Digital · IT Infrastructure & Security · DevOps · Machine Learning · Software Engineering
In short
MLOps Technical Lead accountable for building, deploying, and maintaining machine learning pipelines and operational frameworks in Gurugram, Haryana. This role requires expertise in ML Ops, DevOps tools, Python, infrastructure-as-code, and monitoring solutions to automate workflows and ensure reliable delivery of ML solutions.
Responsibilities
- Implement and maintain ML pipelines using Python, MLflow, Kubeflow Pipelines, and TFX to automate model training, validation, and deployment processes.
- Apply DevOps practices with Jenkins, GitLab CI/CD, CircleCI, and GitHub Actions to streamline CI/CD for machine learning workflows and monitor pipeline health.
- Utilize infrastructure-as-code tools such as Terraform and AWS CloudFormation to provision and manage scalable cloud resources for ML workloads.
- Integrate monitoring solutions like Prometheus, Grafana, ELK Stack, and Fluentd to track model performance, system metrics, and log analytics in production environments.
- Ensure process compliance by using Git, GitHub, GitLab, and Bitbucket for version control and code management within the team.
- Participate in technical discussions and feasibility studies to evaluate technical alternatives and support architecture best practices for ML Ops solutions.
- Prepare and submit status reports to highlight progress, minimize risks, and support project closure activities.
Requirements
- Solid Proficiency In Ml Ops, Including Automation Of Ml Pipelines And Model Lifecycle Management.
- Solid Understanding Of Devops Tools Such As Jenkins, Gitlab Ci/Cd, Circleci, And Github Actions For Workflow Automation.
- Solid Experience With Python For Scripting, Data Processing, And Ml Pipeline Development.
- Solid Knowledge Of Infrastructureascode Tools Like Terraform And Aws Cloudformation For Cloud Resource Management.
- Solid Skills In Monitoring And Logging Tools Including Prometheus, Grafana, Elk Stack, And Fluentd.
- Solid Familiarity With Version Control Systems Such As Git, Github, Gitlab, And Bitbucket.
- Solid Ability To Participate In Technical Discussions And Support Process Compliance Within The Team.
Desired Qualifications
- AWS Certified DevOps Engineer
- Google Professional Machine Learning Engineer
#MLOps#DevOps#Python#CI/CD#Cloud#Infrastructure as Code#Monitoring#Logging#Version Control#Machine Learning
Company
HCLTech
Job Posted
1 month ago
Employment Type
Full Time
WorkMode
On Site
Experience Level
Senior
Locations
Gurugram, India
Applicants
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