Teams at Cerence Inc.

Translate research prototypes into production-grade software, collaborate with R&D, implement CI/CD, perform automated, stability and performance testing, resolve merge conflicts, optimize codebase, apply agentic programming, and maintain release notes and technical documentation while ensuring coding standards and basic ML/ONNX optimizations.

Lead design and training of large-scale transformer and hybrid foundation models across text and multimodal domains. Drive architecture choices (attention variants, MoE), optimize training stability and optimizers, validate scaling laws and compute/data tradeoffs, design loss and alignment strategies (RLHF, DPO, contrastive), and execute distributed training (FSDP, ZeRO-3, tensor/pipeline parallelism) with mixed precision and checkpointing while partnering with ML systems teams.

Lead research and engineering work on LLM-based architectures for dialog, search, and destination entry. Optimize LLMs via prompting and fine-tuning, integrate them with ASR, TTS, and vision systems, and collaborate cross-functionally to deliver performant, resource-constrained solutions for automotive voice assistants.