Senior Generative AI Research Engineer — Remote & Equity

Themeframer; San Francisco (CA); Hybrid; USD 195,000 - 255,000; Full time

Benefits offered by this job

Health & Dental

Equity ownership

Remote-First stipend

Learning budget

Mental Health Days

Annual engineering retreats

Job summary

Theme Framer is seeking an experienced software engineer to join the Generative Systems team in San Francisco. You will design and optimize code-generation workflows, deploy LLM inference pipelines, and collaborate with compiler engineers on AST verification within model feedback loops.

The role emphasizes research-led development, benchmarking, and production readiness for autonomous software systems. We value a strong background in Python, PyTorch, and scalable ML architectures.

Qualifications

• 5+ years of software engineering experience with 3+ years focused on applied ML and LLMs.
• Strong proficiency in Python, PyTorch, and transformer optimization libraries.
• Practical experience deploying LLM inference pipelines in production environments.
• Bachelor's or Master's degree in Computer Science, AI, Mathematics, or equivalent practical experience.

Responsibilities

• Research and implement specialized fine-tuning and inference strategies for code generation.
• Build context compression and semantic retrieval mechanisms for codebase graphs.
• Collaborate with compiler engineers to integrate deterministic AST verification into model feedback loops.
• Publish internal benchmarks and track generative accuracy across real-world application benchmarks.

Skills

Python

PyTorch

LLM architectures

Production deployment

Education

Bachelor's or Master's degree in Computer Science / AI / Mathematics

Tools

transformer optimization libraries

AST parsing

Job description

Theme Framer is seeking an experienced software engineer to join the Generative Systems team in San Francisco. You will design and optimize code-generation workflows, deploy LLM inference pipelines, and collaborate with compiler engineers on AST verification within model feedback loops.

The role emphasizes research-led development, benchmarking, and production readiness for autonomous software systems. We value a strong background in Python, PyTorch, and scalable ML architectures.