22 days ago
Mountain View, CA, USAMid Level
H1B Sponsor
Base Salary
$196k - $221k/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, and training techniques under research and production constraints.
- Own ML system lifecycles from research prototyping through 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 and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment workflows.
- Resolve complex problems involving model behavior, data quality, scaling, and system interactions.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a related field with 2+ years of relevant industry experience; a PhD is preferred.
- 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 ability to evaluate papers and distinguish production-worthy techniques from experimental work.
- 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 architectural decisions in ambiguous problem spaces.
- Experience with or strong interest in agentic systems, tool-use frameworks, or multi-model orchestration.
Benefits
- Hybrid work arrangement is indicated by the #LI-Hybrid designation.
- The role includes a comprehensive total rewards package in addition to base salary.
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.