Software Engineer – Simulation & ML Platform
Intuitive•San Francisco, CA
•$134,600 - $227,700•Onsite
About The Position
As a Senior Software Engineer – Simulation & ML Platform, you will build software platforms supporting simulation-based data generation and machine-learning development for robotic motion AI. You will work closely with Simulation Data Scientists and ML teams responsible for simulation strategy, synthetic-data design, action-model development, sim-to-real evaluation, and machine-learning experimentation. You will translate research and data-science requirements into reliable, scalable, and extendible software systems.
Requirements
- Bachelor's degree in computer science, software engineering, computer engineering, robotics, or a related field, or equivalent practical experience.
- At least 5 years of industry experience developing software for simulation, machine learning, robotics, computer vision, or autonomous systems.
- Experience with high-volume image, video, time-series, or scientific data and formats such as Parquet, Zarr, or HDF5.
- Strong proficiency in Python and at least one additional language such as C++, Java, or TypeScript.
- Experience building data-intensive applications or data-processing pipelines.
- Experience designing and operating production-quality backend or platform systems.
- Experience with asynchronous processing, distributed workers, message queues, or event-driven architectures.
- Strong understanding of API design, data modeling, concurrency, failure handling, and distributed-system fundamentals.
- Experience with Docker, Linux, testing, observability, and production deployment.
Nice To Haves
- Experience with NVIDIA Isaac Sim, Isaac Lab, MuJoCo, Gazebo, PhysX, or another robotics simulation platform.
- Familiarity with USD assets and scene composition.
- Experience with coordinate transforms, robot kinematics, joint states, trajectory representations, sensor synchronization, or closed-loop control.
- Experience with ROS or ROS 2 and GPU-enabled applications or infrastructure.
- Experience with Redis, RabbitMQ, Kafka, Ray, Celery, Kubernetes, Slurm, or cloud batch systems.
- Experience building scientific, engineering, ML, or internal developer tools.
- Experience with PyTorch, JAX, TensorFlow, MLflow, or Weights & Biases.
Responsibilities
- Build and maintain software infrastructure for robotic simulations and machine learning using NVIDIA Isaac Sim, Isaac Lab, MuJoCo, or custom simulation environments.
- Architect scalable pipelines for generating synthetic and procedurally varied robotic interaction data, including APIs, configuration systems, command-line tools, and SDKs for defining and launching simulation workloads.
- Build automated integration and validation pipelines for evolving simulation platforms, physics engines, and the NVIDIA AI ecosystem, enabling adoption of new releases while maintaining compatibility, reproducibility, and stability.
- Develop AI-assisted engineering workflows for automated code refactoring, maintainability analysis, architectural consistency, and CI/CD optimization.
- Create reusable abstractions for robot configurations, tasks, sensors, scene assets, domain randomization, failure injection, data capture, episode termination, and evaluation.
- Build tools that allow data scientists to define experiments without modifying low-level platform code, and support headless, interactive, local, cluster, and cloud-based execution.
- Develop secure, GPU-enabled containerized environments for simulation, data processing, model inference, and experimentation.
- Develop common interfaces for robot state, coordinate frames, actions, trajectories, control commands, sensor observations, timing, and safety status.
- Build tools for importing physical robot logs into analysis and simulation environments, and enable software-in-the-loop, hardware-in-the-loop, and controlled trajectory replay where appropriate.
- Collaborate with controls, embedded, systems, and robotics engineers to manage differences between simulated and physical interfaces.
- Establish standards for software development, testing, documentation, code review, release management, and operational ownership.
Benefits
- Market-competitive compensation packages inclusive of base pay, incentives, benefits, and equity.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
