Staff R&D AI Engineer
Tasks
- Architect reinforcement learning systems for sequential decision making
- Build and optimize computer vision pipelines
- Create multimodal training pipelines
- Design and develop vision language action models
- Develop and fine-tune large language models
- Implement RLHF systems
- Integrate AI models into applications
- Mentor AI engineers and establish best practices
- Optimize model inference for real time edge and cloud
- Present findings and publish research
- Research and prototype novel AI architectures
Perks/Benefits
- 401k match
- Continuing education support
- Equity options
- Flexible time off
- Free parking
- Function health subscription
- Health & wellness stipend
- Health, dental, and vision benefits
- Parental leave
- Supplemental life insurance
Skills/Tech-stack
AI Deployment | AWS | Attention Mechanisms | Azure | Computer Vision | Containerization | Distillation | Distributed Training | Edge AI | Edge AI deployment | Fine Tuning | Google Cloud | Human Feedback | Imitation Learning | Inverse reinforcement learning | Language Processing | Language model fine-tuning | Large Language Model | Large Language Model Fine-Tuning | Learning from Human Feedback | MLOps | Model Fine-tuning | Model Monitoring | Model Optimization | Model versioning | Multimodal Learning | Natural Language | Natural Language Processing | Object Detection | PPO | Pruning | PyTorch | Python | Quantization | Reinforcement Learning | Reinforcement Learning from Human Feedback | SAC | Semantic Segmentation | Sim-to-Real | Synthetic data | TD3 | TensorFlow | Transformers | Visual tracking
Education
Roles
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