Skills this job asks for
LLMsLeadershipA/B testingProduct managementMachine learningPythonPyTorchKubernetesDjango
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
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.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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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.
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✓
What Otter AI INC paid sponsored hires in similar roles5 certified filings for “Research Scientist” (Computer and Information Research Scientists) in CA: $202k–$240k, median $202k.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- 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. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-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 roles
- 5 certified filings for “Research Scientist” (Computer and Information Research Scientists) in CA: $202k–$240k, median $202k. Most were filed at wage level II (40%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
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.
About the role
About the Role
We’re building AI that changes how people capture, understand, and act on conversations and meetings. As Director of AI Research, you will lead research and development across automatic speech recognition (ASR), speaker identification (SID), large language models (LLMs), and audio language models. Your work will shape our AI capabilities, product direction, and long-term research strategy.
This is a hands-on leadership role for someone who combines research depth with experience building and deploying AI systems at scale. You will set technical priorities, guide model and infrastructure decisions, and work directly with the team on challenging research and engineering problems.
Partnering closely with Product, Engineering, and Data teams, you will turn research advances into reliable product capabilities. You will also build the team, experimentation practices, and technical foundation needed to move quickly while maintaining high standards for quality and performance.
Your Impact
• Set the research direction: Define and execute a research roadmap across speech recognition, speaker identification, LLMs, and audio language models, connecting technical advances to user needs and business priorities.
• Own the model lifecycle: Guide data preparation, model architecture, pre-training, post-training, evaluation, and deployment. Establish rigorous methods for measuring quality and improving models using large-scale training data.
• Lead and develop the team: Hire, mentor, and grow a high-performing AI research team. Build a culture of scientific rigor, open collaboration, and clear accountability. Encourage strong viewpoints backed by measurable results and a collaborative mindset that helps the team reach shared decisions.
• Scale training and inference: Drive improvements in model accuracy, latency, reliability, and cost through large-scale training, inference optimization, and efficient use of compute.
• Translate research into products : Evaluate emerging methods, reproduce promising results, and adapt advances from the literature to practical product challenges.
• Shape the AI platform: Partner with Engineering and Data teams to strengthen the infrastructure, tooling, and workflows that support rapid experimentation and reliable deployment.
• Identify new opportunities: Explore AI capabilities that expand what our products can do and support the company’s long-term vision.
We're looking for someone who brings
• A Master’s degree or higher in Computer Science or a related technical field; a PhD is preferred.
• 10+ years of software engineering or AI research and development experience, including 4+ years of experience managing technical teams.
• A track record of leading AI research with meaningful scientific and product impact, supported by publications and deployed systems.
• Deep expertise in speech technologies and LLMs, with hands-on experience in transformer architectures, reinforcement learning, and multimodal model training.
• Experience designing, training, evaluating, and optimizing large-scale ML systems, including distributed training and inference in GPU environments.
• Strong proficiency in Python and PyTorch, with experience using Kubernetes and related infrastructure to run ML workloads at scale.
• Demonstrated ability to set technical direction, develop teams, and collaborate across Research, Product, Engineering, and Data.
• Sound judgment in balancing research ambition, execution speed, and product quality.
• Familiarity with application frameworks and technologies such as Django, FastAPI, and WebSockets.
• A commitment to solving difficult technical problems and delivering measurable value to users.
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About Otter.ai
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