Senior Research Engineer (Python, ML Ops)

A Moving Experience.

Do you have a passion for pushing the boundaries of innovation? Are you excited about AI’s potential to improve the human experience? Then come join the ride!

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 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 are seeking a highly skilled and innovative Senior Software Engineer in the TTS (Text-To-Speech) R&D team to develop TTS products exploiting AI models. The ideal candidate will have a robust background (experience or knowledge) in hands on Python programming and ML Ops. Person should be well-versed in the software engineering practices, version controls such as Git, experience and familiar in deployment, optimization of ai model (throughput, efficiency) and with ML-Ops, not for development of AI model but should expert for integration and optimization = productization.

Your Impact:

• Transitioning AI models from research to product-grade and integrating them into observable services optimized for GPUs, specifically for Text-to-Speech (TTS) applications.

• Develop GPU-accelerated versions of advanced speech AI algorithms like TTS, voice style transfer and neural network-based vocoders etc.

• Identify and address performance bottlenecks, applying optimization techniques to enhance efficiency.

• Work collaboratively with cross-functional teams to introduce new product features and enhance existing products

What You Bring:

• Masters or Bachelors (or equivalent experience) in Computer Science, computer architecture, or related field

• 5+ years of experience, excellent Python programming and software design skills, including debugging, performance analysis, and test design

• Experience with inference Services and productization of AI Models (ML Ops)

• Excellent Debugging abilities spanning multiple software (storage systems, kernels and containers). Familiarity with version control and code review tools

• Background with container technologies such as docker (Preferred)

• Background with AI models for Speech Recognition, speech synthesis, Speech Translation, Machine Translation, TTS (Preferred)

• Experience with Nvidia frameworks and tools for performance measurement and optimization (Preferred)

• Knowledge of GPU programming such as CUDA or OpenCL (preferred)

What We Offer

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

• Annual bonus opportunity

• Insurance coverage as per policy

• Paid time off

• Paid holidays

• Company contribution to the RRSP (Registered Retirement Savings Plan)

• Equity awards for certain positions and levels

• Hybrid work mode is applicable for this 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 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.