Backed by Accel, Insight and Y Combinator.
About the role
We're looking for a Senior Research Engineer to join our Research team, developing and improving the systems behind large-scale distributed training, data processing, and inference. Our goal as an organization is to solve customer problems and improve our products quickly through model development and measurement — and how fast we move depends on how quickly anyone here can run an experiment, measure it, and find out what's wrong. Raising that ceiling is the heart of this role.
What they're looking for
- Expert-level proficiency with JAX and TPUs , including the surrounding ecosystem (Flax, Optax, the XLA compilation pipeline)
- Measurement discipline. You define what success looks like before you start, you stay skeptical of your own results until they hold up, and you treat an unexplained improvement as a problem rather than a win
- Strong experience optimizing inference systems for production, ideally with LLMs or speech models
- Deep understanding of distributed training at scale, modern deep learning systems, and ML infrastructure best practices
- Familiarity with modern inference optimization techniques: continuous batching, KV-cache management, sharding strategies, quantization
- Enthusiasm for refactoring and improving existing systems — you thrive on making products and code faster and better
More about this role
AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for folks truly excited to join a small team and help define the future of the industry.
We are one of the most capital-efficient AI companies on the planet - with under 100 people generating roughly $600K ARR per employee, we sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. That's not an accident; it's a deliberate choice to stay lean, move fast, and give every person on the team outsized ownership and impact. With thousands of customers including Granola, Fireflies, Figure AI, and CallRail, the company has real scale - processing over 2 million hours of audio daily and handling more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven and the trajectory is steep, but the team is still small enough that your fingerprints are on everything.
If you've ever felt buried under layers of bureaucracy, starved...
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