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Cerence Inc.

Senior AI Scientist

Cerence Inc.

Senior AI Scientist designing and training large scale foundation models at Cerence, a leader in automotive voice AI solutions. Involves deep learning, model architecture, and large-scale training.

Posted 7/6/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $123,500 - $197,600 per yearWebsite

About the role

Key responsibilities & impact
  • 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 and compute
  • Apply strong fundamentals in deep learning and representation learning
  • Build models from first principles, not just adapt pre-existing codebases
  • Own optimiser and scheduler choices, including AdamW, Lion, Adafactor
  • Design and experiment with loss functions including next-token prediction and contrastive objectives
  • Design and execute large-scale training using FSDP, ZeRO-3, Tensor parallelism, Pipeline parallelism
  • Apply mixed precision (bf16, fp8) and gradient checkpointing

Requirements

What you’ll need
  • 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 and compute
  • 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
  • Own optimiser and scheduler choices, including AdamW, Lion, Adafactor
  • Understand and debug optimiser instability and gradient pathologies
  • Apply and validate scaling laws
  • Design and experiment with loss functions including next-token prediction and contrastive objectives
  • Design and execute large-scale training using FSDP, ZeRO-3, Tensor parallelism, Pipeline parallelism
  • Apply mixed precision (bf16, fp8) and gradient checkpointing
  • Partner closely with ML systems teams

Benefits

Comp & perks
  • 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

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Hard Skills & Tools
Transformer Architecture DesignRepresentation LearningModel OptimizationGradient CheckpointingMixed Precision (bf16, fp8)Next-Token PredictionContrastive ObjectivesScaling Laws ValidationFSDPZeRO-3