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Bangalore, IN
Actively hiring, first seen by us 6 days agoThis position is not eligible for visa sponsorship
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
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.
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.
From the employer’s posting.
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 6
Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
10 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 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.
Complete your application on jobs.teradyne.com. The employer’s form will show what is required.
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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.
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.
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 OverviewYou 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: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.
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 OfferAt 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.
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.
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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.
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.