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.
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