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We are seeking an experienced Lead/Sr MLOps Engineer with deep expertise in Domino Data Lab to manage and optimize machine learning operations across the entire ML lifecycle. In this role, you will support platform reliability, drive infrastructure automation and ensure seamless deployment and monitoring of machine learning solutions in production environments. Responsibilities - Manage and optimize the Domino Data Lab platform across the machine learning lifecycle - Oversee MLOps processes to support productive model development and operations - Maintenance of Kubernetes clusters and Docker containers for scalable workloads - Implementation of CI/CD pipelines using Jenkins, GitLab and GitHub - Administration of Linux environments to ensure system stability - Provide platform support at L2/L3 levels for end users and stakeholders - Monitoring and troubleshooting of platform issues to minimize downtime - Collaboration with data science teams to streamline machine learning workflows - Deployment and management of solutions across AWS, Azure and GCP Requirements - 5+ years of experience in MLOps or machine learning lifecycle management - Knowledge of Domino Data Lab platform - Expertise in Kubernetes and Docker - Proficiency in Python and R - Skills in CI/CD tools including Jenkins, GitLab and GitHub - Familiarity with AWS, Azure and GCP - Competency in Linux administration - Capability to perform monitoring and troubleshooting - Background in platform support at L2/L3 levels Nice to have - Background in AI/ML engineering - Skills in model deployment and monitoring - Familiarity with data science platform support - Proficiency in infrastructure automation using Terraform and Ansible Location - Hyderabad, Bangalore, Pune, Gurgaon, Chennai, Coimbatore, Jaipur .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.