Senior Software Engineer – Simulation & ML Platform

Intuitive • San Francisco, CA

4d

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. The Senior Software Engineer will translate those 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.
• 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 & ML using NVIDIA Isaac Sim, Isaac Lab, MuJoCo or custom simulation environments.
• Architect scalable pipelines for generating synthetic and procedurally varied robotic interaction data including development of 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 rapid adoption of new releases while maintaining compatibility, reproducibility, and stability across the robotics simulation software stack.
• Develop AI-assisted engineering workflows for automated code refactoring, maintainability analysis, architectural consistency, and CI/CD optimization, enabling readable, modular, and sustainable codebases while improving engineering productivity across large-scale software projects.
• 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.
• 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.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior