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Salary
$185k – $280k per year
Location
Remote (United States)
Seniority
Principal
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Jun 30, 2026. Cerence scores C on the Alion truth index.

Overview
Company
Impact
Profile match
Founded in 2019, Cerence is a global technology company specializing in artificial intelligence and conversational software for the automotive industry. Headquartered in Burlington, Massachusetts, the firm develops voice recognition, natural language understanding, and smart assistant solutions for leading vehicle manufacturers. By integrating intuitive voice controls and connected AI systems into modern automobiles, the organization enhances the overall in-cabin user experience for drivers worldwide.

AI That Moves the World. Careers That Move You Forward.

At Cerence AI, you’ll help transform advanced AI into trusted, real-world solutions that make complex technology - think vehicles, robots, smart manufacturing, and emerging intelligent devices - more natural, reliable, and useful. Building on decades of innovation and global deployment in automotive, we are extending our expertise into new products, markets, and intelligent systems.

As part of our global team, you’ll work alongside leading innovators, researchers, engineers, and business leaders to solve meaningful challenges and turn breakthrough ideas into technology people use every day. You’ll have the opportunity to make a visible impact, help shape Cerence AI’s next chapter, and move your own career forward.

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 Optimisation

  • Implement and evaluate quantisation 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 Optimisation

  • 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
  • Quantisation techniques: INT8/INT4/FP4/FP8, AWQ, GPTQ
  • KV cache optimisation and memory layout design
  • Latency optimisation: 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 401K
  • 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 AI (NASDAQ: CRNC) helps people and intelligent systems work together naturally and reliably. Proven at global scale in automotive, Cerence provides the trusted interaction and action layer connecting people, machines, and intelligent systems. Its AI platform enables natural interaction and dependable action across complex real-world environments where reliability, safety, security, and performance are critical. Working with customers and partners worldwide, Cerence transforms advanced AI into trusted solutions that bridge the gap between AI potential and real-world performance.

For more information, visit www.cerence.ai.

EQUAL OPPORTUNITY EMPLOYER

Cerence is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination on the basis of age, race, color, gender, gender identity, gender expression, sex, sex stereotyping, pregnancy, national origin, ancestry, religion, physical or mental disability, medical condition, marital status, citizenship status, sexual orientation, protected military or veteran status, genetic information and other protected classifications. Cerence Equal Employment Opportunity Policy Statement.

All prospective and current Employees need to remain vigilant when it comes to executing security policies in the workplace. This includes:

- Following workplace security protocols and training programs to familiarize with the ways to maintain a safe workplace.

- Following security procedures to report any suspicious activity.

- Having respect for corporate security procedures to allow those procedures to be effective.

- Adhering to company's compliance and regulations.

- Encouraging to follow a zero tolerance for workplace violence.

- Basic knowledge of information security and data privacy requirements (e.g., how to protect data & how to be handling this data).

- Demonstrative knowledge of information security through internal training programs.

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