2 months ago
Base Salary
$273k - $345k/yr
Responsibilities
- Research and develop reinforcement learning and distillation techniques for trajectory planning.
- Design and deploy multimodal models that translate visual perception and behavioral goals into physical vehicle actuation.
- Develop interactive world models from multi-sensor logs for trajectory re-simulation and counterfactual analysis.
- Adapt autonomous-driving models to novel environments and edge cases.
- Own model post-training, distillation, quantization, profiling, and deployment for low-latency vehicle edge hardware.
- Optimize inference pipelines and hardware-accelerated runtimes while addressing CPU, GPU, and memory bottlenecks.
- Work with hardware, electrical, and firmware teams on carrier boards, sensor interfaces, and edge GPUs.
- Architect pipelines for ingesting, filtering, and extracting rare scenarios from multi-petabyte sensor datasets.
- Build data curation, active learning, data mining, and statistical quality workflows for machine learning pipelines.
- Partner with QA, validation, testing, and simulation teams to detect regressions and convert real-world anomalies into simulation tests.
Requirements
- 10+ years of non-internship professional machine learning engineering experience.
- Deep expertise applying AI Transformers to robotics, physical actuation, or spatiotemporal data.
- Experience designing or training multimodal systems, large-scale VLA models, or generative Diffusion models.
- Strong sensor-fusion experience using camera, LiDAR, and radar data.
- Fluency in PyTorch or JAX and proficiency in Python, with familiarity or robust programming skills in C++.
- Experience with model optimization, distillation, deployment, edge hardware, profiling, or runtime compilation.
- Experience with data curation pipelines, active learning workflows, data mining architectures, or massive physical datasets.
- Familiarity with multi-task learning, Bird's-Eye-View frameworks, representation learning, spatial tokenization, robotics data structures, or low-level sensor interfaces is preferred.
- Ability to structure and derive signal from ambiguous real-world data distributions.
Benefits
- Medical, dental, vision, disability, and life insurance.
- Flexible Spending Account and Health Savings Account options.
- 401(k), equity eligibility, sick time, unlimited flexible time off, and paid holidays.
- Paid parental leave and a pre-tax commuter benefit plan.
- Team lunch in the SoMa office every Tuesday and Thursday.
- Full-time exempt role based in the San Francisco office with onsite work five days per week.
Categories
AI ResearchML Engineering
About Atoms
Atoms develops robotics, software, and infrastructure to automate real-world industrial operations, with offerings focused on food production, mining, and robotic transport platforms. It sells integrated automation systems and platforms—Atoms Food, Atoms Mining, and a transport wheelbase for robots—to industrial customers seeking greater productivity and scalability. The privately held company is headquartered in Los Angeles.