Back to jobs

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

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

Before you apply

Work authorization
Must already have the right to workThis position is not eligible for visa sponsorship

What you’ll work on

Full posting
  • Design and maintain cloud and on-premises GPU infrastructure for simulation and ML training

  • Operate container orchestration and batch job scheduling for large-scale simulation

  • Build and maintain CI/CD pipelines for C++, Python, and web applications

  • Implement MLOps for experiment tracking, model registry, data versioning and deployment

  • Manage storage and data pipelines for terabyte-scale datasets

From the employer’s posting
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
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.
Education & alternatives
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.

Benefits in the posting

Full benefits wording
  • Health insurance and additional benefits.
  • 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.

From the employer’s posting.

Apply at Teradyne

Posting record

Report an error

Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 29, 20266 days ago
Recorded sightings
7
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 6

Similar jobs usually come down between day 6 and day 69.

From 4,284 similar postings that came down. Coming down is not always a hire.

Teradyne is hiring

10 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Bash
  • C++
  • Python
  • AWS
  • Azure
  • Docker
  • GCP
  • Grafana
  • Kubernetes
  • MLflow
  • Snowflake
  • Terraform
Where the posting names them
- 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.
- 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.
- 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.
- 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).
- 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:
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:
- 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.
- Large-scale object storage and data lake design. - Data warehouse platforms such as Snowflake. - GitOps workflows with Argo CD or Flux.
- 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.

Your next step

Complete your application on jobs.teradyne.com. The employer’s form will show what is required.

Applying through SAP SuccessFactors

  • Images (.jpg) aren’t accepted as a resume.

Already applied? Track this application

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Bangalore, IN

- 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.
Work authorization
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.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.