1 year ago
Responsibilities
- Design and develop Vision-Language-Action models integrating visual perception, natural language understanding, and action prediction.
- Architect reinforcement learning systems for sequential decision-making, policy learning, and skill acquisition.
- Build and optimize computer vision pipelines for object detection, segmentation, tracking, and scene understanding.
- Develop and fine-tune large language models for instruction following, reasoning, and task planning.
- Implement RLHF systems and multimodal training pipelines using synthetic and real-world data.
- Research novel multimodal AI architectures and collaborate with engineering teams to integrate and validate models.
- Optimize model inference for real-time edge and cloud applications.
- Lead technical initiatives, mentor junior AI engineers, establish development best practices, and present or publish research findings.
Requirements
- 7+ years of AI/ML engineering experience, including 4+ years focused on deep learning and neural network development.
- Strong understanding of reinforcement learning algorithms and sequential decision-making or control systems.
- Hands-on expertise developing computer vision and natural language processing models.
- Proficiency with PyTorch and/or TensorFlow, Python, distributed training, and model optimization.
- Experience with transformer architectures, attention mechanisms, large language model fine-tuning, and computer vision tasks such as detection, segmentation, and tracking.
- Experience with MLOps practices including model versioning, monitoring, and deployment pipelines.
- Preferred qualifications include a PhD in computer science, robotics, AI/ML, or a related field; VLA or multimodal architecture experience; RLHF, imitation learning, or inverse reinforcement learning; embodied AI or robotics; edge deployment; distributed training; cloud platforms; safety-critical AI; and published AI/ML research.
- Ability to work independently on complex research problems, deliver practical solutions, communicate effectively, and collaborate across engineering teams.
Benefits
- Competitive salary.
- Comprehensive health, dental, and vision benefits for applicable U.S.-based employees.
- 401(k) match, equity options, supplemental life insurance, and parental leave for eligible employees.
- $200/month Health & Wellness stipend and $500/year Function Health subscription.
- Continuing Education support, Flexible Time Off, and free parking for in-office employees.
- Benefits may vary for employees hired outside the United States based on local law, country-specific requirements, and employment platform or entity.
Tech Stack
Categories
AI ResearchML Engineering
