Senior Research Engineer

Who you are

• The ideal candidate has a deep understanding of modern deep learning systems, combined with strong engineering expertise across JAX and TPUs, layer-level optimization, large-scale distributed training, streaming, low-latency and asynchronous inference, inference compilers, and advanced parallelization techniques
• 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
• Appetite for the whole pipeline. Your core strength might be JAX and TPU performance, but when a customer issue traces back to a data problem or an evaluation blind spot, you want to go find it yourself. The people who do well here went deep in one area first, then kept expanding outward
• 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
• Strong Python skills; C++ or Rust experience for kernel-level work is a plus
• Excellent communication and a collaborative mindset — you can clearly explain complex tradeoffs and prioritize high-impact work
• Domain knowledge in Speech-to-Text: ASR architectures, audio processing, streaming inference

What the job involves

• 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. You'll be working inside the pipeline you're improving, not alongside it
• This is a cross-functional role. You'll work closely with our researchers, our infrastructure team, and production engineering — not as a handoff point, but as the person who learns enough of each domain to follow problems through to resolution
• At times you'll train models, run evaluations, and analyze data yourself, both to deliver impact directly and to learn what's worth building to multiply the team's work
• The bar is someone who understands the end-to-end impact they intend to make, measures it from the outset, and would rather find out they were wrong in a week than in a quarter. That discipline is what turns cross-functional ownership into an advantage
• The role is embedded within the Research team
• Raise the team's experimental velocity — make it faster to launch an experiment job, get a number back you can trust, and know what to try next
• Maintain and evolve our JAX training framework, keeping it scalable and efficient for large-scale distributed training runs on TPU
• Improve the data our models learn from: investigating quality issues, building the tooling to surface them, and turning what you find into measurable accuracy gains
• Analyze the accuracy of production models, build evaluation harnesses, and work out which improvements will matter most to customers
• Translate research prototypes into production-ready systems, refactoring and modernizing model architectures and infrastructure along the way
• Optimize production inference for speech language models, both from a serving architecture perspective and through advanced techniques such as quantization and speculative decoding
• Investigate and resolve performance bottlenecks across the stack, from low-level kernels (XLA, Pallas) to high-level system design
• Partner with researchers, infrastructure, and production engineering to trace problems to their real source and ship fixes that hold

Benefits

• Home office stipend: We invest in our people first and offer competitive salaries across all roles andEvery new team member gets U$1,000 to improve their home office. We want to make sure everyone has the setup to do their best work. locations
• Equity: We want our team members to have skin in the game and an opportunity to see long-term returns on the hard work they are putting in. To that end, every team member receives a generous equity grant
• Premium benefit offerings: We offer premium medical, dental, and vision plans and cover up to 100% of the premiums for both the employee and their family. We also offer opportunities to contribute to an HSA or FSA, short-term and long-term disability coverage, and life insurance
• Unlimited PTO: We offer a flexible PTO policy to all team members and encourage everyone to take time off to recharge, do something fun, and spend time with loved ones
• Team offsites: We have team and company-wide retreats in amazing locations to give everyone an opportunity to meet in person, collaborate, and build working relationships that make us a better team
• Global remote team: We hire the best person for the job, regardless of location. Our remote-first culture allows team members to make an impact from anywhere in the world
• Diversity and inclusion: We celebrate diversity and are committed to creating an inclusive environment for all employees. We are proud to be an equal-opportunity workplace
• Flexible schedule: Strong teams are built on mutual trust and accountability. We believe in giving our team members ownership over their work and a flexible schedule to allow them to operate at their highest potential