Sr. Principal Software Scientist

Cerence; United States; Hybrid; USD 185,000 - 280,000; Full time

Benefits offered by this job

Annual bonus

Insurance coverage

RRSP contribution

Equity awards

Remote/hybrid work

Paid time off

Job summary

Cerence is a global leader in AI for mobility, seeking a Senior Principal AI Scientist in Generative AI to drive next-generation models. You will design, train, and scale large transformer models, optimize training stability, and define architecture direction with cross‑functional teams worldwide. This role offers impact across automotive AI, with opportunities to shape scalable, innovative solutions in a collaborative, fast-paced environment.

Qualifications

• Strong theoretical and practical understanding of modern deep learning.
• Hands-on experience training large models from scratch.
• Ability to reason about optimization, not just tune hyperparameters.
• Comfort operating in ambiguous, research-driven environments.

Responsibilities

• Own transformer architectures and attention mechanisms across text and multimodal models.
• Design and modify transformer architectures (RoPE, ALiBi, GQA, MoE).
• Diagnose training instabilities and improve scaling behavior.
• Define technical direction for next-generation models and scaling laws.

Skills

Deep learning fundamentals

Transformer architectures

Optimization & training dynamics

Distributed training

Model scaling laws

Loss design

MoE / mixture of experts

Multimodal modeling

Tools

FSDP

ZeRO-3

Tensor parallelism

Job description

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 SeniorPrincipalAI Scientist in Generative AI who is ready to drive the future of mobility with us!

What You Will Work On

• Design and trainlarge‑scaletransformer and hybrid foundation models

• Own model architecture choices across text, multimodal, and emerging paradigms

• Diagnose and resolvetraining instabilities at scale

• Navigate scaling tradeoffs across data, compute, and architecture

• Define the technical direction fornext‑generationmodels

Core Responsibilities

Deep Learning & Transformer Foundations

• Apply strong fundamentals in deep learning and representation learning

• Design andmodifytransformer architectures, including:

• Attention variants

• RoPE,ALiBi

• Grouped Query Attention (GQA)

• Mixture‑of‑Experts(MoE)

• Build modelsfrom first principles, not just adaptpre‑existingcodebases

OptimisationDynamics & Training Stability

• Own optimizer and scheduler choices, including:

• AdamW

• Lion

• Adafactor

• Learning‑rateand warmup schedulers

• Understand and debug:

• Optimizer instability

• Gradient pathologies

• Divergence at large scale

Scaling Laws & Compute Tradeoffs

• Apply andvalidatescaling laws

• NavigateChinchilla‑stylecompute vs data tradeoffs

• Make informed decisions about model size, dataset size, and training duration

Loss Functions & Alignment

• Design and experiment with loss functions including:

• Next‑tokenprediction

• Contrastive objectives

• RLHF,DPO,GRPO

• Understand how loss design impacts convergence, generalization, and alignment

Distributed Foundation Model Training

• Design and executelarge‑scaletraining using:

• FSDP

• ZeRO‑3

• Tensor parallelism

• Pipeline parallelism

• Apply

• Mixed precision (bf16,fp8)

• Gradient checkpointing

• Partner closely with ML systems teams whileretainingarchitectural ownership

Architecture Innovation

• Explore and implement novel model designs, including:

• MoErouting strategies

• Multimodal fusion architectures

• SSM / hybrid architectures

• Design architectures with KV cache efficiency and inference implications in mind

What Success Looks Like

• Trainingremainsstable as models scale in size and complexity

• Architectural decisions are principled and defensible

• Models converge faster and generalize better due to architecture and optimisation choices

• Failure modes are understood, not mysterious

• The organization develops truein‑housefoundation modelexpertise

Required Experience & Skills

Strongly Required

• Deep theoretical and practical understanding of modern deep learning

• Hands‑onexperience traininglarge models from scratch

• Ability to reason about optimization, not just tune hyperparameters

• Comfortoperatingin ambiguous,research‑drivenenvironments

Critical Technical Skills

• Transformer internals and attention mechanisms

• Optimisationalgorithms and training dynamics

• Scaling laws and compute/data tradeoffs

• Distributed training strategies and mixed precision

• Architecture innovation for large,real‑worldmodels

Common ProblemsYou’llBe Solving

• Why training diverges at scale

• How optimizer dynamics interact with architecture

• When scaling laws break down

• The real tradeoffs between data, compute, and model design

What we offer

We offer a generous compensation and benefits package (in addition to the base salary), including:

• Salary range$185,000.00 - $280,000.00 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.

AsCerencelooks to the future and continues an ambitious growth agenda,we need someonetojointheteam and help build the future of voice and AI in cars. This is an exciting opportunity to joinCerence’spassionate, 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 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.

- 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.