Sr. Principal Software Engineer

A Moving Experience. Who is Cerence AI?   Cerence AI is the global leader in AI for transportation, specialized in building AI and voice-powered companions for cars, two-wheelers, and more that enable people to focus on what matters most. With over 500 million cars shipped with Cerence AI's technology, we partner with leading automakers (such as Volkswagen, Mercedes, Audi, Toyota and many more), mobility providers, and technology companies to power intuitive, integrated experiences that create safer, more connected, and more enjoyable journeys for drivers and passengers alike.   Our Driving Force    Our team is dedicated to pushing the boundaries of AI innovation, working around the globe with headquarters in Burlington, Massachusetts, USA and 16 other offices across Europe, Asia, and North America. We bring together diverse backgrounds, and varied skill sets with the shared goal of advancing the next generation of transportation user experiences. Our culture is customer-centric, collaborative, fast-paced, and fun, with continuous opportunities for learning and development to support your career growth.   Interested in having a significant impact in a dynamic industry with a high-performing global team? We’re looking for an exceptional Senior   Principal   Software Engineer who is ready to drive the future of mobility with us!   Job Description: What You Will Work On   Optimize and deploy  high ‑ performance LLM inference pipelines   Own inference runtimes across  data center, edge, and embedded platforms   Push model performance through quantization, kernel fusion, and cache optimization   Drive latency and throughput improvements that directly impact production products   Enable efficient, reliable deployment without external vendor dependency   Core Responsibilities   Inference Engines & Runtime   Build deep expertise and ownership of:   vLLM  TensorRT‑LLM  llama.cpp  QAIRT  Extend and tune inference engines using  custom CUDA kernels   Adapt runtimes for constrained and embedded deployment environments   Quantization & Numerical   Optimi s ation   Implement and evaluate   quanti s ation   strategies:   INT8, INT4, FP4, FP8, mixed precision  AWQ  GPTQ  Balance accuracy, latency, memory footprint, and throughput   KV Cache Optimization   Optimize key–value cache performance through:   Paging  Prefix caching  Cache ‑ aware  memory layout design  Reduce memory pressure while sustaining high throughput   Latency & Throughput Optimi s ation   Design and tune:   Batching strategies  Continuous batching  Speculative decoding  Optimize tail latency and tokens/sec under real production traffic patterns   What Success Looks Like   Models deploy efficiently on  edge and embedded devices , not just servers   Tokens/sec significantly outperform baseline implementations   End ‑ to ‑ end latency is minimized and predictable   Inference cost per request is materially reduced   The company is no longer dependent on partners for inference optimization   Required Experience & Skills   Strongly Required   Proven experience optimizing  ML inference performance in production   Deep understanding of  GPU architecture and memory hierarchies   Hands ‑ on experience with CUDA and low ‑ level performance tuning   Experience deploying models beyond research environments   Critical Technical Skills   Inference engines:  vLLM ,  TensorRT ‑ LLM, llama.cpp, QAIRT   CUDA kernel development and profiling   Quanti s ation   techniques: INT8/INT4/FP4/FP8, AWQ, GPTQ   KV cache   optimi s ation   and memory layout design   Latency   optimi s ation : batching, speculative decoding, continuous batching   Common Problems You’ll Be Solving   Deploy efficiently on  edge or embedded targets  Achieve competitive  tokens/sec  Reduce and stabilize inference latency   You will be responsible for  closing these gaps , creating a major competitive advantage.   What we offer   We offer a generous compensation and benefits package (in addition to the base salary), including:   Salary range  $185,000.00 USD - $280,000.00 USD It is not typical for offers to be made at or near the top of the range. The actual salary will be determined based on experience and other job-related factors.   Annual bonus opportunity   Insurance coverage (medical, dental, vision, life, and disability)   Paid time off   Paid holidays   Company contribution to the RRSP (Registered Retirement Savings Plan)   Equity awards for certain positions and levels   Remote and/or hybrid work available depending on the position   All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable, and may be amended, terminated, or replaced from time to time.   Cerence Inc. (Nasdaq: CRNC and  www.cerence.com ) is the global industry leader in creating unique, moving experiences for the automotive world. Spun out from Nuance in October 2019, Cerence is a new, independent company that has quickly gained traction as a leader in the automotive voice assistant space, working with all of the world’s leading automakers – from Ford and Fiat Chrysler to Daimler, Audi and BMW to Geely and SAIC – to transform how a car feels, responds and learns. Its track record is built on more than 20 years of industry experience and leadership and more than 500 million cars on the road today across more than 70 languages.    As Cerence looks to the future and continues an ambitious growth agenda, we need someone to join the team and help build the future of voice and AI in cars. This is an exciting opportunity to join Cerence’s passionate, dedicated, global team and be a part of meaningful innovation in a rapidly growing industry.   EQUAL OPPORTUNITY EMPLOYER Cerence is firmly committed to Equal Employment Opportunity (EEO) and to complia