At a Glance
- Tasks: Own the performance of our inference stack and optimise model serving efficiency.
- Company: Join a forward-thinking AI company focused on real-time adaptive intelligence.
- Benefits: Flexible work, travel stipend, lunch allowance, and comprehensive medical benefits.
- Other info: Collaborative environment with opportunities for personal and professional growth.
- Why this job: Make a real impact in AI by optimising performance and shaping the future of intelligence.
- Qualifications: 5+ years in ML systems, strong Python skills, and experience with performance engineering.
The predicted salary is between 72000 - 88000 £ per year.
The role
You'll own the cost and performance of our inference stack. Your work will determine how efficiently we serve models as workloads, traffic, and hardware change.
You'll work closely with the engineers operating the serving fleet while owning the core performance levers: caching, batching, quantization, decoding, and kernel-level optimization.
Success means improving throughput and latency without compromising reliability or model quality.
Responsibilities
- Improve throughput, cost, and tail latency through KV-cache management, continuous batching, speculative decoding, and quantization.
- Optimize long-context prefill and decode workloads based on real production traffic.
- Tune routing between our infrastructure and external providers based on cost, capacity, and performance.
- Work within serving engines such as v LLM, SGLang, and Tensor RT-LLM, going below the framework when needed.
- Build profiling and measurement systems that show where time, memory, and compute are being spent.
Qualifications
- 5+ years in ML systems, inference infrastructure, or performance engineering, with measurable improvements in cost or latency.
- Deep understanding of model serving, including prefill and decode, memory bandwidth, batching, and concurrency.
- Production experience with serving engines such as v LLM, SGLang, or Tensor RT-LLM.
- Strong Python skills and proficiency in C++, Rust, or another systems language.
- Experience with GPU performance, including CUDA, NCCL, mixed precision, memory layout, kernels, or quantization.
Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas.
You don't need to be perfect, but you do need to be adaptable.
About Us
Most AI is frozen in place - it doesn't adapt to the world.
We think that's backwards.
Our mandate is to build efficient intelligence that evolves in real-time.
Our vision is AI systems that are flexible, personalized, and accessible to everyone.
We believe efficiency is what makes this possible - it's how we expand access and ensure innovation benefits the many, not the few.
We believe in talent density: bringing together the best and most driven individuals to push the boundaries of continual adaptation.
We're looking for builders and creative thinkers ready to shape the next era of intelligence.
Benefits
- Flexible work: In-person collaboration in the Bay Area, a distributed global-first team, and team offsites.
- Adaption
Passport: Annual travel stipend to explore a country you've never visited.
We're building intelligence that evolves alongside you, so we encourage you to keep expanding your horizons.
- Lunch Stipend: Weekly meal allowance for take-out or grocery delivery.
- Well-Being: Comprehensive medical benefits and generous paid time off.
- #J-18808-Ljbffr
Inference Performance Engineer employer: Adaption
As a Senior Research Scientist at our innovative AI company, you'll be part of a dynamic team that values technical excellence and real-world impact. We offer a flexible work environment in the Bay Area, comprehensive medical benefits, and unique perks like an annual travel stipend to broaden your horizons. Join us to collaborate with top talent and contribute to cutting-edge research that shapes the future of intelligent systems.
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We think this is how you could land Inference Performance Engineer
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We think you need these skills to ace Inference Performance Engineer
Some tips for your application 🫡
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Adaption. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Adaption
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
