Senior Machine Learning Engineer - Generative Models
Applied Intuition22 hours ago
Base Salary
$185k - $260k/yr
Responsibilities
- Develop and advance diffusion and video-generation models for Neural Simulation.
- Build controllable generation conditioned on scene layout, camera pose, actors, and trajectories.
- Create temporally consistent, multi-camera video generation and augment real-world logs with new scenarios, actors, weather, and lighting.
- Combine generative models with neural reconstruction to improve simulated-scene fidelity and coverage.
- Scale training and inference of large generative models for production workloads.
- Define evaluation metrics, benchmarks, and validation workflows measuring realism, temporal consistency, controllability, and the sim-to-real gap.
- Work with customers to understand pain points and implement technical solutions in the Neural Simulation product.
- Collaborate with infrastructure, autonomy, research, and product teams on end-to-end solutions.
- Own critical technical components and influence architecture and product decisions.
Requirements
- At least 5 years of experience developing and shipping machine-learning or computer-vision systems.
- Bachelor’s degree in computer science, physics, robotics, or equivalent experience.
- Hands-on experience with diffusion models and video generation, including latent and video diffusion models or diffusion transformers.
- Strong foundation in generative modeling and deep learning, including training and fine-tuning large models.
- Proficiency in Python and PyTorch.
- Ability to turn research ideas into robust, production-quality software.
- Preferred experience with learning-based 3D reconstruction, including 3D Gaussian Splatting, NeRFs, or feed-forward Gaussian Splatting.
- Preferred background in computer vision or computer graphics, including SfM, SLAM, photogrammetry, rendering, rasterization, or ray tracing.
- Preferred track record of shipping ML products with defined evaluation metrics and benchmarks.
- Preferred experience in autonomous driving or robotics and with camera, LiDAR, or radar data.
- Preferred experience with 3D-aware or multi-view-consistent generation, world models, distributed training, inference optimization, distillation, or efficient sampling.
- Programming experience in C++ and/or CUDA is preferred.
- Peer-reviewed research at CVPR, ICCV/ECCV, NeurIPS, ICLR, ICML, or SIGGRAPH is preferred.
- A Master’s degree or PhD in computer science, physics, robotics, or a related field is preferred.
Benefits
- Full-time employees primarily work from an Applied Intuition office five days per week, with occasional remote work and schedule flexibility.
- The company provides reasonable accommodations for applicants with disabilities, disabled veterans, and other medical conditions.
Categories
About Applied Intuition
Applied Intuition builds software tools, infrastructure, and operating systems for developing, testing, and deploying autonomous and driver-assistance systems across automotive, trucking, defense, construction, mining, and agriculture. It sells enterprise software and services including simulation, sensor data management, HD mapping, and a vehicle OS to OEMs and government customers. Founded in 2017 and headquartered in Sunnyvale, California, it counts 18 of the top 20 global automakers and the U.S. military among its users.