Jobs / United States / Otter AI INC
Senior Machine Learning Engineer
Otter AI INC · 🇺🇸 Mountain View, CA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 30 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Otter AI INC paid sponsored hires in similar roles19 certified filings for “Senior Software Engineer” (Software Developers) in CA: $188k–$226k, median $188k. Most were filed at wage level II (42%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Otter AI INC
The US Department of Labor certified 30 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Otter AI INC →
About the role
The Opportunity 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 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. Your Impact • 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. We're Looking for Someone Who • Holds a Bachelor’s or Master’s degree in Computer Science or a related field with 5+ years of relevant industry experience; PhD is preferred. • Has 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. • Demonstrates strong command of modern ML research, with the ability to critically evaluate new papers and drive innovation by identifying what is production-worthy versus experimental. • Has experience deploying, scaling, monitoring, and operating ML systems in production across training, inference, and serving infrastructure. • 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. • 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. About Otter.ai We are in the business of shaping the future of work. Our mission is to make conversations more valuable. With over 1B meetings transcribed, Otter.ai is the world’s leading tool for meeting transcription, summarization, and collaboration. Using artificial intelligence, Otter generates real-time automated meeting notes, summaries, and other insights from in-person and virtual meetings - turning meetings into access