22 days ago
Base Salary
$230k - $265k/yr
Responsibilities
- Architect, build, and evolve large-scale SID, ASR, NLP, and LLM systems for summarization, chat, and speech understanding.
- Lead training, fine-tuning, post-training, and inference strategies for large language and speech models using PyTorch and/or JAX.
- Design and improve model architectures, loss functions, decoding strategies, and training techniques.
- Own ML system lifecycles from research prototyping through production deployment, monitoring, iteration, and maintenance.
- Partner with product and infrastructure teams to translate research into scalable production systems.
- Improve model performance, robustness, observability, and operational excellence using conversational data at scale.
- Set technical direction for ML infrastructure, data pipelines, evaluation frameworks, and deployment workflows.
- Resolve complex problems involving model behavior, data quality, scaling, and system interactions.
- Lead technical projects, influence engineering standards, review designs, and mentor other engineers.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a related field and 5+ years of relevant industry experience.
- Deep hands-on experience building and fine-tuning large language or foundation models.
- Production experience with ASR, TTS, multimodal, or modern LLM/NLP systems.
- Strong command of modern ML research and the ability to evaluate research for production readiness.
- 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, and labeling strategies.
- Ability to lead technical projects independently and make architectural decisions in ambiguous problem spaces.
- Experience with or strong interest in agentic systems, tool-use frameworks, or multi-model orchestration.
- PhD is preferred.
Benefits
- Hybrid work arrangement.
- Equal opportunity and inclusive workplace.
- Comprehensive total rewards package; the stated salary is base salary and excludes other rewards components.
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.