Otter.ai is shaping the future of work by making conversations more valuable. With over 1 billion meetings transcribed, Otter.ai is the world's leading tool for meeting transcription, summarization, and collaboration. Leveraging artificial intelligence, Otter provides real-time automated meeting notes, summaries, and insights from in-person and virtual meetings, transforming conversations into accessible, collaborative, and actionable data. The company is backed by early investors in Google, DeepMind, Zoom, and Tesla. Otter.ai is an equal opportunity employer committed to diversity and inclusivity.

About the Position

Introduction

Otter.ai is seeking a Staff Machine Learning Engineer to join its core AI team. In this role, you will lead projects to build and deploy cutting-edge AI technology, transforming innovative research into production-ready features for Otter's summarization and conversational intelligence products.

Responsibilities

Architect, build, and evolve large-scale SID / ASR / NLP / LLM systems for summarization, chat, and speech understanding.
Lead the design and implementation of 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 for speech and language models.
Own end-to-end ML system lifecycles from research prototyping to production deployment, monitoring, and maintenance.
Partner with product and infrastructure teams to translate research into scalable, production-grade systems.
Drive system-level improvements in model performance, robustness, observability, and operational excellence.
Set technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment workflows in a cloud environment.
Identify and resolve complex, ambiguous problems in model behavior, data quality, scaling, and system interactions.
Mentor and elevate other engineers, influencing team standards and technical decision-making.
Influence applied research and technical roadmaps by identifying and validating promising speech and multimodal modeling approaches.

Requirements

Bachelor’s or Master’s degree in Computer Science or a related field with 10+ years of relevant industry experience; 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 understanding of model failure modes and trade-offs.
Strong command of modern ML research, with the ability to critically evaluate papers and drive innovation.
Extensive experience deploying, scaling, monitoring, and operating ML systems in production.
Comfortable working with large-scale speech and conversational datasets, including data preprocessing, augmentation, quality analysis, and labeling strategies.
Highly effective at cross-functional collaboration, delivering outcomes with product, infrastructure, research, and data teams.
Ability to lead technical projects independently, driving clarity and making sound architectural decisions.

Nice to Have

Experience with or strong interest in agentic systems, tool-use frameworks, or multi-model orchestration.
Demonstrated ability to influence beyond your immediate team.
Experience with personalization, recommendation systems, or user modeling.