Machine Learning Engineer

Required Skills

CI/CD
Kubernetes
Machine Learning

Job Description

Job Title: Machine Learning Engineer

Job Type: Full-time(8hours/day) Contract

Location: Hybrid -Delhi, (Gurugram office 3 days/week)


Job Summary:

Join our customer's team as a Machine Learning Engineer and help deliver end-to-end machine learning solutions using the latest cloud and container technologies. As part of a dynamic group, you’ll bridge data science innovation with scalable deployment, empowering impactful ML projects in a modern, hybrid work environment.


Key Responsibilities:

• Design, build, and maintain machine learning pipelines using CI/CD methodologies on Kubernetes.

• Deploy, manage, and optimize Kubeflow and other MLOps platforms to operationalize data science projects.

• Implement GitOps workflows with Argo to ensure automated, repeatable deployments.

• Develop cloud-native infrastructure as code (IaC) and manage environments within AWS.

• Collaborate closely with data scientists and engineers to transition models from research to production.

• Ensure robust security, monitoring, and debugging of deployed ML systems.

• Contribute to documentation and promote best practices in written and verbal communication within the team.


Required Skills and Qualifications:

• Strong experience with Kubernetes for building and operating scalable ML solutions.

• Deep understanding of CI/CD, with hands-on experience in cloud-native ML workloads.

• Proficiency in deploying and managing Kubeflow and/or AWS SageMaker.

• Solid background with AWS Cloud infrastructure and services.

• Expertise in Python and Bash scripting for automation and system integration.

• Familiarity with infrastructure as code (IaC) and GitOps tools such as Argo.

• Excellent written and verbal communication skills; ability to clearly convey technical concepts.


Preferred Qualifications:

• Prior experience with ML security and debugging best practices.

• Hands-on experience with end-to-end operationalization of data science projects on Kubernetes.

• Exposure to continuous testing (CT) in ML workflows.

Apply now

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Please note that by applying & completing our interview process, you will be added to our talent pool. This means you’ll be considered for this and all other possible roles that may match your skills. These potential opportunities will be sent your way as a micro1 certified candidate.

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