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Staff Machine Learning Engineer

Otter.ai· Engineering
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Mountain View, CA$278k - $330kfull-timePosted 7mo ago

About the role

Senior-level ML engineering role focused on building and deploying scalable ML systems (ASR, NLP, LLM) for Otter’s meeting summarization and conversational intelligence products. Emphasis on end-to-end ML lifecycle, productionizing research, and driving technical direction in ML infrastructure and deployment workflows.

Responsibilities

  • 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.
  • Influence applied research and technical roadmaps by identifying promising speech and multimodal modeling approaches, and driving their validation and adoption into production systems.

Qualifications

  • 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 command of modern ML research, with ability to critically evaluate new papers and drive innovation by identifying what is production-worthy versus experimental.
  • Experience deploying, scaling, monitoring, and operating ML systems in production across training, inference, and serving infrastructure.
  • Comfort with large-scale speech and conversational datasets, including data preprocessing, augmentation, quality analysis, and labeling strategies to support model training and evaluation.
  • Ability to lead technical projects independently, driving clarity in ambiguous problem spaces and making sound architectural decisions.
  • Experience or strong interest in agentic systems, tool-use frameworks, or multi-model orchestration.

Skills

Required:Large-scale ML model developmentML infrastructure and deploymentPyTorch and/or JAXSpeech and language modeling

Benefits

  • Salary range: $278,000 to $330,000 USD per year.
  • Comprehensive total rewards package (base salary plus benefits not detailed in excerpt).
Last updated Aug 19, 2026. Interested? Apply on the company site.

About Otter.ai

Turn conversations into transcripts

Otter is the AI Notetaker that builds your knowledge base and powers your workflow with transcription, automated summaries, AI Chat, and more.

transcriptionAI NotetakersummariesAI Chatmeetingsproductivityintegrations
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