Member of Technical Staff - Research
Trajectory · San Francisco
Infrastructureonsite
At a glance
Highlights
- Build post-training stack letting customer models learn from live workflows.
- Own end-to-end experiments turning product telemetry into learnable signals.
- Work directly with founders to define culture and architecture.
Ideal candidate
Creative ML researcher energized by open-ended experimentation and building continual-learning systems from real product use with founders.
Requirements
- Experience training or serving large language models
- Experience building RL environments or evaluation suites for LLMs
- Proficiency in PyTorch, JAX, or similar ML frameworks
- Strong experimental design skills
- Master's / research experience
- Background in pre- or post-training RL for LLMs
- Experience with high-performance computing or large-scale clusters
- Contributions to open-source ML research or infrastructure
- Demonstrated technical creativity (research, OSS, side projects)
Lab profile
About Trajectory
Builds a continual-learning platform helping production models learn from real workflows.
What they build
- Continual-learning platform
- Post-training stack for LLMs and agents
- SDK and API surfaces
Known for
- Continual learning from production telemetry
- Custom LLM and agent training and serving
- Novel continual-learning algorithms
- ML training and inference infrastructure optimization
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