Job description

Why AssemblyAI AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. We have a lab, and we also power our own models in our own proprietary inference environment. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for the best talent we can find to join a rapidly scaling team that's defining the future of the industry. We are one of the most capital-efficient AI companies on the planet - and are rapidly approaching $1M ARR per employee. We sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. We have thousands of customers building with us including the top startups and world renown enterprises, and are serving at tremendous scale: we process over 2 million hours of audio daily and handle more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven, the revenue is durable, and the growth trajectory is steep and getting steeper. We have a super flat culture and expect our employees' to be deeply intimate with the details at all levels. If you’ve ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build, this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you’ll actually know everyone’s name. About the Role AssemblyAI builds the foundational speech models behind the Voice AI products our customers build. The people who train those models and build the systems that serve them are some of the hardest people in tech to hire; and we need to hire a lot more of them in 2027. We’re looking for a Senior Technical Recruiter to own hiring for our Research team and a portfolio of senior Engineering roles: Researchers, Research Engineers, and ML Engineers. You’ll work directly with our research and engineering leaders, and you’ll be expected to understand the work well enough to find, assess, and close people others can’t. What You’ll Do Own full-cycle recruiting for Research and senior Engineering roles, from intake through offer and close Build deep, outbound-first pipelines: map talent at frontier labs, speech and audio teams, and academic groups; track publications, open-source contributors, and conference speakers Partner with research and engineering leaders to define profiles, calibrate on bar, and design quality, efficient interview loops Run thoughtful screens with technical candidates and give hiring managers sharp, evidence-based reads Lead complex closes: competing offers from large labs, equity conversations, and international candidates, in partnership with the People team Build long-term relationships with candidates who aren’t ready to move yet Use data and AI tooling to work faster: smarter sourcing, cleaner Greenhouse pipelines, and clear reporting on funnel health Help the team scale: interviewer training, structured kits, and a candidate experience that reflects how much we care about the work What You’ll Need 5+ years of technical recruiting, with a track record of hiring ML researchers, research engineers, or ML/infrastructure engineers at AI labs, AI-native startups, or top tech companies A strong outbound sourcing practice and a network in the ML/AI research community Enough technical fluency to talk credibly about model training, evaluation, and inference with researchers, and to tell a strong profile from a keyword match Experience closing senior, sought-after candidates against competing offers, including equity-heavy packages Comfort with Greenhouse, LinkedIn Recruiter, JuiceBox (or similar), and modern AI sourcing tools Self-direction: you find the highest-impact work and do it without waiting to be asked Pay Transparency: AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity across our team. Our salary ranges are set to be competitive for our size, stage, and industry, and reflect just one component of the full compensation, benefits, and rewards we offer. Salary determinations consider a variety of factors, including relevant experience, technical depth, skills demonstrated during the interview process, and maintaining internal equity with peers on the team. The range shared below represents a general expectation for the posted position. However, we are open to considering candidates who may fall above or below the outlined experience level—in those cases, we will communicate any adjustments to the expected salary range. The range provided applies to candidates located in the United States . For candidates outside of the U.S., compensation ranges may differ; any adjustments will be communicated throughout the interview process. Compensation: $170,000–$200,000 The expected cash compensation for this role is listed above. Our total compensation package includes competitive equity grants and 100% employer-paid benefits. Using AI in your interview If you’re selected for an interview, please read our Candidate AI Guidance . It explains how you can use AI at each stage of our process, from your application and take-home to the interviews themselves. GDPR privacy notice If you’re applying from the EU or UK, please review our Job Applicant Privacy Notice before applying. Keep exploring AssemblyAI Transcribe: Speech-to-Text | Streaming Speech-to-Text Understand: Speech Understanding | LLM Gateway Interact: Voice Agent API | Dictation API Try our models in the Playground See how 50+ LLMs rank on real voice tasks: Voice Standard Bench Watch us on YouTube

Requirements

Must-haves

Why AssemblyAI
What You’ll Do
Own full-cycle recruiting for Research and senior Engineering roles, from intake through offer and close
Build deep, outbound-first pipelines: map talent at frontier labs, speech and audio teams, and academic groups; track publications, open-source contributors, and conference speakers
Partner with research and engineering leaders to define profiles, calibrate on bar, and design quality, efficient interview loops
Run thoughtful screens with technical candidates and give hiring managers sharp, evidence-based reads
Lead complex closes: competing offers from large labs, equity conversations, and international candidates, in partnership with the People team
Build long-term relationships with candidates who aren’t ready to move yet
Use data and AI tooling to work faster: smarter sourcing, cleaner Greenhouse pipelines, and clear reporting on funnel health
Help the team scale: interviewer training, structured kits, and a candidate experience that reflects how much we care about the work
What You’ll Need
5+ years of technical recruiting, with a track record of hiring ML researchers, research engineers, or ML/infrastructure engineers at AI labs, AI-native startups, or top tech companies
A strong outbound sourcing practice and a network in the ML/AI research community
Enough technical fluency to talk credibly about model training, evaluation, and inference with researchers, and to tell a strong profile from a keyword match
Experience closing senior, sought-after candidates against competing offers, including equity-heavy packages
Comfort with Greenhouse, LinkedIn Recruiter, JuiceBox (or similar), and modern AI sourcing tools
Self-direction: you find the highest-impact work and do it without waiting to be asked

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiapimlllm

Platform: greenhouse
Effort: quick