Principal Software Engineer - Simulation Data, Validation & Infrastructure
$147,760 per year
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Posted today
SENIORITY
Lead
SALARY
$147,760 per year
About the role
- Advanced software engineering experience using Python and one or more of C++, C#, Java, Go, or Node.js.
- Experience with APIs, distributed systems, containers, automated testing, CI/CD, source control, and observability. Principal Engineer Job Description Page 3Experience with cloud platforms and cloud-native architectures, including Docker and Kubernetes.
- Demonstrated ability to lead architecture and technical delivery across multiple teams.
- Strong communication, mentoring, problem-solving, and cross-functional collaboration skills.
- Experience using AI-assisted development tools such as GitHub Copilot, Claude, or Cursor.
- Deep experience with CoreWeave or comparable GPU cloud platforms, Kubernetes, Docker, NVIDIA Container Toolkit, GPU operators, scheduling, and workload optimization.
- Experience supporting NVIDIA Omniverse, Isaac Sim, Isaac Lab, Newton, Cosmos, Replicator, training, inference, and synthetic-data workloads.
- Experience with CUDA-aware systems, multi-GPU execution, distributed workloads, job queues, autoscaling, and GPU utilization monitoring.
- Experience with telemetry, time-series, sensor, image, video, LiDAR, segmentation, depth, map, and simulation ground-truth data.
- Experience with SQL, NoSQL, object storage, time-series databases, Kafka, Spark, Flink, or comparable technologies.
- Experience with Terraform, Helm, GitOps, CI/CD, secrets management, security controls, and reproducible environments.
- Experience with Open
- Telemetry, Prometheus, Grafana, logging, tracing, cost monitoring, and service-level objectives.
- Knowledge of statistical validation, uncertainty, tolerance analysis, model correlation, and traceable acceptance criteria.
- Seven or more years of software, data, platform, cloud, HPC, or infrastructure engineering experience.
- Five or more years building production data pipelines or accelerated-computing platforms.
- Experience processing large-scale machine telemetry, sensor, simulation, or Physical AI datasets.
- Experience designing secure, reproducible GPU platforms for multiple engineering teams.
- Preferred Technology StackCoreWeave | Kubernetes | NVIDIA GPUs | CUDA | Docker | Terraform | Helm | Omniverse | Isaac Sim | Newton | Replicator | Cosmos | Prometheus | Grafana
- Success Measures
- Establish a clear reference architecture and technical roadmap for the capability area.
- Deliver reusable platform components and measurable engineering outcomes within the first 12 months.
- Improve quality, automation, scalability, and cross-team adoption while reducing duplicated solutions.
- Develop technical depth across the broader engineering organization through mentoring and standards.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
