Hands-on AI Engineer prototyping and refining LLM-based features, upgrading capabilities with prompt engineering and fine-tuning, while creating evaluations and migration processes for Fathom's meeting AI product. Requires Python proficiency, analytics skills, and Master's degree.
Salary not listed
HybridML Engineering
About the role
Responsibilities
Upgrade existing features to be smarter and/or faster using prompt engineering and latest models.
Improve or create new evaluations for existing features.
Prototype new AI features addressing valuable use cases.
Fine-tune models for specific needs.
Develop processes to speed up migration to new AI models.
Requirements
Hard Skills
Experience with prompt engineering to achieve outstanding and reliable LLM outcomes.
Proficient in Python for end-to-end prototypes.
Foundational analytics (data manipulation in Python or SQL).
Master's degree in a related field.
Previous experience in fine-tuning LLMs highly desirable.
Soft Skills
Attention to detail and high scrutiny for impactful LLM applications.
Curiosity-driven, pragmatic, focus on results.
Generalist mindset, ability to dive deep.
Resilience for complex problems.
Openness to disagreement, commitment to decisions.
Characterize, analyze, and optimize performance of state-of-the-art AI models on Cerebras' wafer-scale hardware. Build performance models, optimize kernels and compilers, debug runtime behavior, and develop visualization tools to influence next-gen AI architecture.
Salary not listed
On-site3+ YOEML Engineering
Research Engineer, Privacy
OpenAISan Francisco, CA
Research Engineer on OpenAI's Privacy team designing and prototyping privacy-preserving ML algorithms like differential privacy and federated learning at scale. Requires hands-on PETs experience, fluency in PyTorch/JAX, and a track record implementing or publishing novel privacy work.
380k – 445k/yr
HybridML Engineering
Research Engineer
ConsoleSan Francisco, CA
Research Engineer building self-improving AI agent systems at Console. Develop eval/optimization loops, fine-tune specialist models, and improve agent reasoning over enterprise context using production data to drive measurable gains in quality, latency, and reliability.
200k – 350k/yr
On-siteML Engineering
Software Engineer, AI Platform
NotionSan Francisco, CA +1
Build and scale the shared AI platform foundations at Notion, enabling fast and safe shipping of AI products. Requires experience with LLM/ML platforms, strong ownership, and comfort across backend, infrastructure, and product code.
180k – 201k/yr
Hybrid5+ YOEML Engineering
Machine Learning Engineer
LiftoffCalifornia
Machine Learning Engineer building statistical models, optimization systems, and experiments for mobile ad tech economics on the Revenue Engine team. Requires PhD in CS/ML/Economics and industry experience applying ML or economics at scale.