Artificial Intelligence Researcher

Are you passionate about pushing the boundaries of AI? Do you dream of building cutting‑edge models that rival OpenAI and Google—but with a twist? Imagine those same models running entirely locally on a phone, delivering unmatched efficiency and accessibility to everyone. If that excites you, we want you to join our mission.

We’re developing the next generation of AI foundation models with a focus on efficiency. Our small but mighty team is crafting a revolutionary large language model (LLM) architecture designed to deliver top performance while running seamlessly on any device—no cloud required.

We’re looking for self‑motivated AI researchers and engineers to help us redefine the future of AI. Whether you’re passionate about building optimization theory, fine‑tuning high‑performance systems, or diving deep into low‑level GPU design, you’ll have the opportunity to leave your mark on something truly transformative.

Impact and Scale:
Be part of a 5‑person team with big ambitions. We’ve just raised $10M in funding, and we’re aiming to hit the top 10 global leaderboards in the coming months.

World‑Class Team:
Work alongside top minds, including former researchers from Harvard, Dartmouth, and infrastructure leads from Cohere and NVIDIA.

Ownership and Influence:
Own entire domains, from post‑training optimization to inference systems. You’ll have direct influence on millions in compute spend and help shape the team’s future.

Mission‑Driven Work:
Help us create efficient, accessible AI that puts the power of LLMs into the hands of anyone, everywhere.

We’re seeking candidates with expertise in machine learning, large language models (LLMs), and AI infrastructure. You don’t need to check every box, but relevant experience includes:

• Hands‑on experience training and optimizing large‑scale LLMs at labs like OpenAI, Google, Mistral, or Z.ai.
• Contributions to community projects such as NanoGPT, Speedrun, or Marin.
• Deep understanding of model parallelism and large‑scale AI infrastructure.

• Academic or personal work on instruction data curation, tool use, or post‑training optimizations.
• Experience with reinforcement learning for language models, including environments, infrastructure, or training.

• Contributions to frameworks like vLLM, SGLang, Dynamo, or Mega Kernels.
• Strong systems‑level understanding of batching, KV cache optimization, and long‑context management.

• Papers or academic work on optimization, data strategies, or training methodologies.
• Hands‑on experience monitoring, maintaining, and optimizing large‑scale training runs.
• Software/hardware co‑design to maximize training throughput.

Revolutionary Vision:
Be part of a team creating game‑changing, efficient models that bring world‑class AI capabilities to any device.

Autonomy:
Lead research efforts and guide entire domains with massive ownership over your projects.

Growth Opportunity:
Shape the future of the company, build the team around you, and take on leadership roles as we grow.

Are you ready to make AI more efficient, accessible, and transformative for the world?