Yasp is pioneering the future of software development with a compiler that leverages agentic AI
for advanced optimization and code generation. We are looking for a visionary Research Engineer - AI for Code to join our team and drive the core innovation that will define the next generation of our technology. We don’t draw boundaries between research and engineering. We are creative thinkers and relentless prototypers who live at the bleeding edge of AI research and engineering. Together, we explore, invent, and ship novel technology that pushes beyond the state of the art for accelerating deep learning models.

What You’ll Do:

• Research, build, tune, and ship novel agentic AI and LLM based methods for complex
  problem-solving, planning, and code synthesis.

• Evaluate the efficacy of AI driven compilation and optimization via benchmarking across
  diverse datasets, ensuring robust real-world performance.

• Stay up to date with the publication landscape (e.g., NeurIPS, ICLR, ICML), open-source
  projects, and industry trends to identify the way to move forward.

• Identify, steer and apply effective agent patterns, prompt-engineering and post-training
  strategies with an experiment-driven scientific mindset.

• Develop clean production ready code, tooling and automations with an engineering
  mindset.

• Work with a talented team towards breakthroughs in AI for code.

What We're Looking For:

• Master’s or PhD in Computer Science/Maths/Physics with a focus on AI/ML, or
  equivalent practical experience.

• Exceptional prior work in AI/ML, ideally involving LLMs or Agents to solve a complex
  task.

• Solid understanding of machine learning principles and the ability to apply them to new
  domains.

• Fluent engineering (Python, PyTorch/TensorFlow/Jax, agentic AI frameworks, LLM
  tooling and APIs, Docker, GCP/AWS/Azure, software development best practices).

• Passion for good scientific practice, blending clean formal thinking and good
  communication with exacting engineering.

Bonus Points:

• Experience with fine-tuning LLMs and Reinforcement Learning (RL), especially in the
  context of tool use or optimization.

• Familiarity with compiler design, program synthesis, or code generation principles (MLIR,
  TVM, LLVM).

• Experience with GPU accelerated kernels (e.g. CUDA, OpenCL, ROCm) for Nvidia and
  AMD GPUs.

• Contributions to major open-source AI frameworks or research projects.

Perks and Benefits:

• Competitive salary.

• Comprehensive health benefits (including dental).

• Opportunities for professional development and growth.

• Flexible work hours.

• Dynamic and collaborative work environment.

• Cutting-edge software and hardware platforms.