Machine Learning Engineer, Otter.ai
$196-221k
Office located in Mountain View, CA
AI notetaker, transcription & insights
Open for applications
AI notetaker, transcription & insights
201-500 employees
Open for applications
$196-221k
Office located in Mountain View, CA
201-500 employees
Company mission
To create smarter tools that free people up to do their best work.
Role
Who you are
- Holds a Bachelor’s or Master’s degree in Computer Science or a related field with 2+ years of relevant industry experience; PhD is preferred
- Has deep, hands-on experience building, fine-tuning, and post-training large language models or other foundation models, including an understanding of failure modes and trade-offs
- Demonstrates strong command of modern ML research, with the ability to critically evaluate new papers and decide what is production-worthy versus experimental
- Has interest in creating innovation and advancing applied research
- Has extensive experience deploying, monitoring, and operating ML systems in production, including model versioning, rollback strategies, and performance regression detection
- Is comfortable working with large-scale speech and conversational datasets, including data preprocessing, augmentation, quality analysis, and labeling strategies to support model training and evaluation
- Has experience scaling ML systems across training, inference, and serving infrastructure while balancing cost, latency, and reliability constraints
- Is highly effective at cross-functional collaboration, working end-to-end with product, infra, research, and data teams to deliver outcomes—not just models
- Can lead technical projects independently, driving clarity in ambiguous problem spaces and making sound architectural decisions
- Has experience with or strong interest in agentic systems, tool-use frameworks, or multi-model orchestration
- Has significant experience with at least one of the following areas: (1) Speech recognition (ASR), (2) Text-to-speech (TTS), (3) Multimodal (speech/text) foundation models, or (4) modern LLM NLP tasks (e.g., summarization, dialogue, speech understanding), especially in real-world production settings
- Experience with personalization, recommendation systems, or user modeling is a plus
What the job involves
- Do you want to lead projects to build and deploy cutting-edge AI technology to help people get unparalleled value from meetings and conversations
- Join our core AI team responsible for ML and work alongside industry-veteran scientists and engineers
- As a Senior/Staff Machine Learning Engineer, you’ll bring your strong software engineering mindset to machine learning in order to scale and optimize our ML systems—creating and transforming innovative research into production-ready features that power Otter’s summarization and conversational intelligence products
- Architect, build, and evolve large-scale SID / ASR / NLP / LLM systems that power mission-critical product experiences including summarization, chat, and speech understanding across millions of conversations
- 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, making principled trade-offs across quality, latency, cost, and reliability
- Design and improve model architectures, loss functions, decoding strategies, and training techniques for speech and language models, informed by both research and production constraints
- Own end-to-end ML system lifecycles, from research prototyping through production deployment, monitoring, iteration, and long-term maintenance
- Partner deeply with product, and infrastructure teams to develop and translate cutting-edge research into scalable, production-grade systems that deliver measurable user and business impact
- Drive system-level improvements in model performance, robustness, observability, and operational excellence using real-world conversational data at scale
- 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, often before they surface as user-visible issues
- Mentor and elevate other engineers, influencing team standards, reviewing designs, and contributing to a culture of strong technical decision-making and execution
Our take
Otter specifically thought of business professionals who are running from one meeting to the next, while juggling multiple projects with various teams. The company's technology integrates with platforms like Zoom, providing a way to record meetings and convert speech to text in real-time. It then streamlines communications for smarter, more collaborative, and more productive meetings—the first use of conversational AI to turn meetings into an actionable workflow.
This allows people to benefit from captioning, as well as teams to have a written record of the conversation, which can be edited and shared. Its AI can also highlight and comment on important sections of a meeting transcript, and automatically tag action items. In addition to businesses, students and universities – including UCLA, Tulane, and Western Kentucky – use the tool to increase accessibility.
The platform is used in more than 230 countries and has transcribed over 100 million meetings. Otter is far from alone in the audio transcription market, estimated to be worth nearly $41.89 billion by 2030, with Google’s free transcription tool posing a potential threat, as well as competitors such as Rev.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
27% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Feb 2021
$10m
CONVERTIBLE
Feb 2021
$40m
SERIES B
Total funding: $73m
Company benefits
- Compensation: With highly competitive salaries and equity option packages, everyone's an owner here.
- Hybrid Working: You can mix and match working from our Mountain View or San Francisco office, plus a couple days from home.
- Social Gatherings: Quarterly gatherings in the Bay Area for some team real fun and authentic connection.
- Health and Wellness: Comprehensive medical, dental, vision, life insurance, disability, and wellness benefits that start the first day you do.
- PTO: Start with a minimum of 15 days of paid time off, plus up to 18 weeks for maternity leave and 8 weeks for paternity leave.
- 401(k): Plans to help meet your retirement goals because we care about your future.
Company HQ
Old Mountain View, Mountain View, CA
Leadership
Sam Liang
(Co-Founder & CEO)Earned a PhD from Stanford and then joined Cisco as a Senior Software Engineer. Worked as a Tech Lead at Google and is a member of the Forbes Technology Council.
Yun Fu
(Co-Founder & CTO)Has a PhD in Computer Science from Duke. Worked as Yahoo's Principal Software Engineer and was Head of Infrastructure at Particle Media.
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