about 3 hours ago
Base Salary
$251k - $310k/yr
Responsibilities
- Conduct comprehensive experimentation to train and deploy multimodal LLMs and world models for 3D perception.
- Collaborate with engineering and research teams to deploy new models and implement efficient workflows.
- Apply techniques such as quantization, pruning, and knowledge distillation.
- Develop and maintain scalable data pipelines for training and evaluation.
- Design and implement evaluation frameworks for perception models.
- Create infrastructure for large-scale model distillation and bulk-inference pipelines.
- Experiment with model partitioning and sharding strategies.
- Build tools for performance analysis and debugging of ML models.
Requirements
- PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar field.
- 4+ years of industry or post-doc research experience in reinforcement learning or foundation models.
- Proficiency in implementing scalable model training flows.
- Experience with JAX, Flax, and potentially TensorFlow/PyTorch.
- Hands-on experience optimizing training and inference of Transformer architectures.
Benefits
- Health, dental, vision, life, and disability insurance.
- 401(k) retirement plan with company match.
- 20 days of vacation per year, accruing at 6.15 hours per pay period.
- 40 hours of sick time per year.
- 28-30 weeks of maternity leave and 18 weeks of baby bonding leave.
- 13 paid holidays per year.