Senior Principal Software Scientist

🕒 3 days ago

🍂 Massachusetts – Remote

🍂 Massachusetts – Remote

💵 $185k - $280k / year

⏰ Full Time

🟠 Senior

🧬 Research Scientist

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Cerence Inc.

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2019

🤖 Artificial Intelligence

🚗 Transport

💰 Grant on 2020-12

Artificial Intelligence • Transport • Automotive

Cerence Inc. is a global company focused on providing AI-powered solutions, particularly in the automotive industry. They specialize in conversational and generative AI technologies that create intelligent, natural, and personalized interactions between humans and vehicles. With innovations like their proprietary automotive large language models, Cerence enhances user experiences across various forms of transport including cars, two-wheelers, and trucks. The company has over 500 million vehicles shipped with its AI technology, serving more than 80 OEMs and Tier 1 customers worldwide. Cerence is dedicated to continuous advancements in AI, aiming to revolutionize in-car user experiences through fast delivery and seamless integration of their solutions.

📋 Description

• Design and train large-scale transformer and hybrid foundation models • Own model architecture choices across text, multimodal, and emerging paradigms • Diagnose and resolve training instabilities at scale • Navigate scaling tradeoffs across data, compute, and architecture • Define the technical direction for next-generation models • Apply strong fundamentals in deep learning and representation learning • Design and modify transformer architectures, including: Attention variants, RoPE, ALiBi, Grouped Query Attention (GQA), Mixture-of-Experts (MoE) • Build models from first principles, not just adapt pre-existing codebases • Own optimizer and scheduler choices, including: AdamW, Lion, Adafactor • Understand and debug optimizer instability, gradient pathologies, divergence at large scale • Validate scaling laws and navigate compute vs. data tradeoffs

🎯 Requirements

• Strongly Required: Deep 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 • Critical Technical Skills: Transformer internals and attention mechanisms • Optimization algorithms and training dynamics • Scaling laws and compute/data tradeoffs • Distributed training strategies and mixed precision • Architecture innovation for large, real-world models

🏖️ Benefits

• 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