About Genesis AI
Genesis AI builds the simulation platform powering the next generation of robotics and embodied AI. Our flagship product, Genesis World , is a unified multi-physics simulation engine paired with Nyx , our in-house GPU-accelerated, path-traced photorealistic renderer. Together they provide a platform for training robotics and embodied AI at scale; letting teams simulate complex physical worlds with high fidelity and speed, from a laptop to datacenter-grade GPUs, and close the gap between simulation and the real world.
About the Role
We're hiring a Senior QA Engineer to own quality across Nyx and the Genesis World engines. You'll split your time evenly between hands-on exploratory testing and enhancing our automated test infrastructure. Because both systems run on GPUs and underpin robotics training and scientific workloads, correctness goes beyond "does it run": it's about visual fidelity, numerical accuracy, determinism, and reproducibility across hardware.
We're especially looking for someone with strong knowledge of 3D environments, assets, and rendering , who can reason about what "visually and physically correct" actually means.
What You'll Do
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Maintain and evolve our automated test suites for the Nyx renderer and the Genesis World physics engine.
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Develop image-comparison / perceptual-diff tooling to catch rendering regressions, and validation harnesses to catch simulation drift.
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Validate numerical correctness, determinism, and reproducibility across GPUs, drivers, and CUDA versions.
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Perform exploratory and manual testing on 3D scenes, assets, and complex multi-physics scenarios that are hard to automate.
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Set up quality gates in CI for prebuilt wheels across platforms (Linux, Windows, Python 3.10–3.13).
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Triage, reproduce, and clearly document defects; partner with engineers on root cause.
What We're Looking For
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5+ years in software QA, with strong experience in both test automation and exploratory testing.
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Solid 3D environment and asset knowledge, with familiarity with rendering and simulation/physics.
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Strong Python and C++ skills; comfortable reading performance-sensitive code.
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Understanding of testing challenges in GPU and floating-point systems; non-determinism, tolerance-based assertions, hardware/driver variance.
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Experience building test infrastructure in CI/CD and managing cross-platform builds.
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Excellent debugging instincts and clear, reproducible bug reports.
Nice to Have
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Experience with GPU programming, or ray/path tracing concepts.
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Background in computer graphics (PBR, color management, perceptual image metrics).
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Familiarity with physics or scientific simulation.
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Robotics or sim-to-real experience.