AI Research Scientist - SLM and Voice Advanced (Senior)

Remote Work: Hybrid Overview: At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges.

Being a part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are a part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.

You'll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about – locally and globally.

Come make an impact every day at Zebra.

We are seeking a highly skilled and motivated Research Scientist to join our "Zebra Nation" of innovators, focusing on the frontiers of Small Language Models (SLMs) and Voice AI. The ideal candidate will bridge the gap between cutting-edge research and real-world product impact. You will be responsible for designing, developing, and deploying high-performance AI solutions that run seamlessly on both edge devices and cloud infrastructure. Your work will involve pioneering new methods in model distillation and alignment to create efficient and powerful models that allow our customers to Sense, Analyse, and Act in real-time .

Responsibilities:

• Advanced Model Development: Design and implement novel machine learning models with a special focus on Small Language Models (SLMs) and Automatic Speech Recognition (ASR). Develop robust speech processing for noisy environments (ASR, TTS) and domain-specific language models.
• Model Optimization and Alignment: Lead efforts in model compression and efficiency. Utilize advanced techniques such as knowledge distillation, quantization, and pruning to create lightweight models for resource-constrained edge devices. Implement and experiment with state-of-the-art model alignment techniques, including RLHF and DPO.
• Research and Innovation: Push the boundaries of what is possible in AI by translating academic theory into production-grade technology. Conduct research that advances the state-of-the-art in SLMs and ASR, with opportunities to patent inventions and publish findings at top-tier conferences.
• Data-Centric AI: Architect and manage data pipelines for large-scale datasets. Implement algorithms for automatic data curation, cleaning, and pre-processing to ensure high-quality inputs for model training and fine-tuning.
• Prototype to Production: Lead the transition of research prototypes into scalable, production-ready solutions by collaborating closely with engineering and product teams.
• Collaboration and Mentorship: Collaborate effectively in a team environment on shared codebases using Git/GitHub. Mentor junior scientists and engineers, fostering a culture of technical excellence, curiosity, and innovation.

Qualifications: Core Qualifications

• Education: PhD or Master's degree in Computer Science, Artificial Intelligence, a related technical field, or equivalent practical experience.

Core Experience:

• Proven experience in designing and implementing machine learning models, particularly in Small Language Models (SLMs) and/or Speech Recognition (ASR).
• Demonstrated, hands-on experience with advanced model optimization techniques, including knowledge distillation, quantization, and pruning.
• Deep understanding and practical experience with model alignment methods such as RLHF, DPO, or similar techniques.
• Programming: Strong proficiency in Python and extensive experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
• Fundamentals: Solid theoretical and practical understanding of deep learning, reinforcement learning, and statistical modeling.

Preferred Qualifications:

• A strong track record of publications in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, Interspeech, CVPR).
• Familiarity with the Hugging Face ecosystem (Transformers, Datasets, TRL).
• Experience using tools such as Hydra for configuration management and Weights & Biases for experiment tracking.
• Familiarity with MLOps best practices (Docker, Kubernetes, W&B) to support reproducible research and scalable deployment.
• Strong communication skills to articulate complex technical concepts to product stakeholders.

Benefits & Culture

• Impact: Work on enterprise-grade systems that are deployed in the real world at a massive scale.
• Professional Development: Receive strong support for continuous learning and attending academic conferences.
• Innovation: Join a culture that champions new thinking and creativity, allowing you to advance exploratory research.
• Collaboration: Work in a high-energy, collaborative environment with world-class experts in Computer Vision, Language Models, and Speech Recognition.

Zebra offers a comprehensive benefits package, including generous paid time off and pension matching, private healthcare and wellbeing support, learning & development opportunities.

• 25 days of vacation
• Up to 32 hours paid time off per year to volunteer with a charity of your choice
• Training and personal development in soft skills and hard skills, access to our internal learning portal and internal career opportunities within Zebra departments
• Employee referral bonus for bringing New Talent to Zebra
• Pension Scheme with a matched contribution up to 7%
• Private medical and dental covers
• Cycle to work scheme
• Employee Assistance Program

To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.

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