Machine Learning Engineer

Otterai

Mountain View, CA, United States
Base: $196,000 to $221,000 usd py; bonus/equity: n...
On-site
Build and deploy ai technology
Ml systems scaling and optimization
Large-scale sid/asr/nlp/llm systems
Otter.ai is seeking a Machine Learning Engineer to join their AI team in Mountain View, CA. The role focuses on developing and deploying advanced AI technologies for meeting transcription and summarization, requiring extensive experience in machine learning systems

Job Summary

  • 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.
  • Own end-to-end ML system lifecycles, from research prototyping through production deployment, monitoring, iteration, and long-term maintenance.
  • Mentor and elevate other engineers, influencing team standards, reviewing designs, and contributing to a culture of strong technical decision-making and execution.

Matching Summary

Match Score: 85

Otter.ai is seeking a Machine Learning Engineer to join their AI team in Mountain View, CA. The role focuses on developing and deploying advanced AI technologies for meeting transcription and summarization, requiring extensive experience in machine learning systems.

Salary

Base: $196,000 to $221,000 USD per year; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • build and deploy AI technology
  • ML systems scaling and optimization
  • large-scale SID/ASR/NLP/LLM systems
  • PyTorch and/or JAX
  • end-to-end ML system lifecycles
  • production ML systems deployment
  • large-scale speech and conversational datasets
  • agentic systems or tool-use frameworks

Nice-to-have

  • advance applied research
  • personalization, recommendation systems, or user modeling

Key Requirements

  • 3+ years of relevant industry experience
  • Bachelor’s or Master’s degree in Computer Science or related field
  • deep, hands-on experience building, fine-tuning, post-training LLMs
  • strong command of modern ML research
  • extensive experience deploying, monitoring, operating ML systems
  • experience scaling ML systems

Work Rights

Not specified

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