7 months ago
Seattle, WA, USAMid Level / Senior
Responsibilities
- Design, build, and iterate on experimental ML pipelines for foundational model development.
- Implement and train large-scale models, including transformers and diffusion architectures.
- Develop and evaluate reinforcement learning algorithms for autonomous behaviors.
- Rapidly prototype and deploy research ideas into working code.
- Collaborate with cross-functional teams to integrate ML components into real-world systems.
- Stay updated on the latest AI research and share insights internally and externally.
Requirements
- Master’s degree in Machine Learning, AI, Computer Science, or a related field.
- Minimum 3 years of experience in applied ML research and software engineering.
- Hands-on experience training large-scale ML models such as transformers or diffusion models.
- Strong understanding of reinforcement learning fundamentals and applications.
- Proficiency in Python and ML frameworks like PyTorch, JAX, or TensorFlow.
- Proven ability to write clean, efficient, and scalable code for fast iteration.
- Excellent collaboration and communication skills.
- Willingness to occasionally travel.
- Must have and maintain US work authorization.
Benefits
- Relocation stipend for candidates moving to Seattle from over 50 miles away.