MLops Engineer - Simulation (Universal Robots, Bangalore - India)

Universal Robots; Bengaluru; On-site; INR 2,800,000 - 4,000,000; Full time

Benefits offered by this job

Health insurance

On-site collaboration with product and

Global team, local impact

Job summary

Universal Robots, part of Teradyne Robotics, is seeking a DevOps/MLOps Engineer in Bengaluru to design and operate GPU-heavy simulation infrastructure. You will manage cloud and on-prem pipelines, implement MLOps, and optimize resources for scalable robot simulation and ML training.

The role requires 4+ years in DevOps/SRE/MLOps, strong Docker/Kubernetes, and cloud experience. Collaboration with global R&D teams is essential, with on-site work in Bangalore.

Qualifications

• Bachelor's or Master’s in CS, Engineering, or related field.
• 4+ years in DevOps, SRE, or MLOps.
• Hands-on Docker and Kubernetes in production.
• Experience with at least one major cloud platform (AWS, Azure, or GCP).
• Infrastructure as code tools like Terraform, Pulumi, or CloudFormation.

Responsibilities

• Design, build, and maintain cloud and on-prem infrastructure for GPU-heavy workloads.
• Operate container orchestration and batch scheduling for large-scale simulations.
• Build and maintain CI/CD pipelines for C++, Python, and web apps.
• Implement MLOps for experiment tracking, model registry, data versioning.
• Manage storage and data pipelines for terabyte-scale datasets.
• Ensure security, access control, and compliance across infra.
• Collaborate with simulation, dataset, and research teams to speed up iteration.

Skills

Docker & Kubernetes

Python & Bash

CI/CD pipelines

Cloud platforms (AWS/GCP/Azure)

Linux administration

Education

Bachelor's or Master's degree in CS/Engineering

Tools

Terraform

Pulumi

GitHub Actions

Job description

Our Purpose

TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought and in our workforce. Our employees are supported to innovate and learn something new every day. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.

Universal Robots, part of Teradyne Robotics, is the world market leader in collaborative robots (cobots), making products that empower our customers and positively transform the way they work. Teradyne Robotics is a division of Teradyne and includes Universal Robots and Mobile Industrial Robots (MiR). Our global R&D organization of 200+ engineers builds the software and systems behind every cobot we ship.

Opportunity Overview

You will join a team of talented and passionate engineers developing, testing, and optimizing the software and systems that let us simulate our robot platforms and train the models that run on them.

As a DevOps/MLOps Engineer on the Simulation team, you will build and run the infrastructure behind large-scale robot simulation, synthetic data generation, and ML training. Simulating UR cobots and MiR mobile robots at scale depends on reliable GPU compute, fast and repeatable pipelines, and a well‑managed lifecycle for data and models — and that is what you will own.

This is a hands‑on engineering role at the intersection of cloud infrastructure, GPU computing, and machine learning operations. You will work with Kubernetes, infrastructure as code, and MLOps tooling across cloud and on‑premises environments, and collaborate closely with simulation engineers, dataset engineers, research scientists, and the wider R&D organization in Denmark and Bangalore.

Your Responsibilities And Tasks Include

• Design, build, and maintain cloud and on-premises infrastructure for GPU‑heavy simulation, rendering, and ML training workloads.
• Operate container orchestration and job scheduling for large‑scale batch simulation and synthetic data generation.
• Build and maintain CI/CD pipelines for C++, Python, and web applications, including build caching, artifact management, and release automation.
• Implement MLOps capabilities for experiment tracking, model registry, data versioning, and model deployment.
• Manage storage and data pipelines for terabyte‑scale datasets with high‑throughput access.
• Implement infrastructure as code, along with monitoring, logging, and alerting across all environments.
• Optimise GPU utilisation and cloud costs, and provide clear visibility of resource usage.
• Ensure security, access control, and compliance best practices across infrastructure and pipelines.
• Support simulation environment versioning so runs are reproducible and traceable.
• Write clean, well‑tested, and documented code and configuration, and participate actively in code reviews.
• Partner with simulation, dataset, and research teams to remove infrastructure bottlenecks and speed up iteration.

All About You

We seek individuals who share our passion and determination. Our commitment to customer success drives us to go the extra mile. If you're ready to join us in this mission, take a closer look at the minimum criteria for the position.

We value diversity in culture, competence, and experience. We expect you to bring a number of qualifications to be considered for this role.

Mandatory Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 4+ years of professional experience in DevOps, site reliability engineering, or MLOps.
• Strong hands‑on experience with Docker and Kubernetes in production.
• Practical experience with at least one major cloud platform (AWS, Azure, or GCP).
• Proficiency with infrastructure as code tools such as Terraform, Pulumi, or CloudFormation.
• Strong scripting skills in Python and Bash, and solid Linux systems administration.
• Experience building CI/CD pipelines with GitHub Actions, GitLab CI, Jenkins, or Argo.
• Experience with monitoring and observability tools such as Prometheus, Grafana, or the ELK stack.

Proficiency required in at least four of the following qualifications:

• Managing GPU clusters, including NVIDIA drivers, CUDA, the GPU Operator, and MIG.
• HPC or batch schedulers such as Slurm, Volcano, or Kueue.
• MLOps tools such as MLflow, Weights & Biases, Kubeflow, or DVC.
• Distributed computing frameworks such as Ray.
• Distributed ML training at scale.
• Large‑scale object storage and data lake design.
• Data warehouse platforms such as Snowflake.
• GitOps workflows with Argo CD or Flux.
• Cloud cost optimisation and FinOps practices.
• Robotics simulation workloads, NVIDIA Isaac Sim, or Omniverse deployment.
• Security hardening, secrets management, and identity and access management.

Personal Attributes

Candidates should demonstrate ambition, organizational skills, and adaptability. Independence, initiative, responsibility, and ownership are vital. A pragmatic approach, commitment to continuous learning, and dedication to work quality are expected.

What We Offer

At Universal Robots we set a high bar and in return we provide an exciting career in a fast‑growing, technology‑driven company where you work alongside skilled and talented colleagues from around the world.

• Global team, local impact — Be part of a world‑class R&D organisation managed from Denmark while making a tangible difference from our Bangalore office every day.
• Growth and development — A manager with continuous focus on team spirit, employee development, and skill building.
• Empowerment — Ownership of your work and the products you help create; we trust our engineers to make informed decisions that benefit the organisation.
• Health insurance and additional benefits.
• On‑site collaboration with co‑located product and software teams, fostering strong working relationships and rapid feedback.

We are only considering candidates local to position location and are unable to provide relocation for this position.

This position is not eligible for visa sponsorship.