22 days ago
Base Salary
$278k - $330k/yr
Responsibilities
- Architect, build, and evolve large-scale SID, ASR, NLP, and LLM systems for summarization, chat, and speech understanding.
- Design and implement training, fine-tuning, post-training, and inference strategies for large language and speech models using PyTorch and/or JAX.
- Improve model architectures, loss functions, decoding strategies, training techniques, performance, robustness, observability, and reliability.
- Own ML system lifecycles from research prototyping through production deployment, monitoring, iteration, and maintenance.
- Set technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and cloud deployment workflows.
- Lead technical projects, make architectural decisions in ambiguous problem spaces, and identify and resolve complex model, data, scaling, and systems issues.
- Partner with product, infrastructure, and applied research teams to deliver scalable production systems and influence technical roadmaps.
- Mentor engineers, review designs, and elevate team standards and technical decision-making.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a related field, with 10+ years of relevant industry experience; a PhD is preferred.
- Deep hands-on experience building and fine-tuning large language or foundation models, with production experience in ASR, TTS, multimodal, or modern LLM/NLP systems.
- Strong command of modern machine learning research and the ability to assess which approaches are production-ready.
- Experience deploying, scaling, monitoring, and operating ML systems across training, inference, and serving infrastructure.
- Experience with large-scale speech and conversational datasets, including preprocessing, augmentation, quality analysis, labeling strategies, training, and evaluation.
- Ability to lead technical projects independently and make sound architectural decisions in ambiguous environments.
- Experience with or strong interest in agentic systems, tool-use frameworks, or multi-model orchestration.
Benefits
- Hybrid work arrangement, as indicated by the #LI-Hybrid posting designation.
- Base salary range of $278,000 to $330,000 USD per year, with additional total rewards components not specified.
Tech Stack
Categories
About Otter.ai
Otter.ai is the Conversational Knowledge Engine built for the modern enterprise, giving AI agents the organizational context to act on by connecting thousands of conversations across thousands of people. Available on desktop on Mac and Windows, iPhone, Android, web. Used by more than 35 million people, across over one billion meetings, generating more than 30 million action items. The pioneer of the AI meeting assistant category. Backed by early investors in Google, Zoom, and Tesla. Headquartered in Mountain View, California.