Member of Technical Staff, Applied AI – Speech

Location: Fully remote; no relocation to San Francisco is required. Close collaboration with the Applied AI team at the San Francisco headquarters. The team typically works around 60 hours per week, beginning at 8:00 AM, with four days spent collaborating in person at the San Francisco office.

Salary: $300,000–$450,000 plus equity.

Company

hirify.global builds AI agents for regulated financial services, automating loan servicing, compliance, collections, recovery, insurance claims, and disputes for banks, captives, and specialty lenders. Its voice product handles live collections and servicing conversations across voice, SMS, email, and chat with real-time compliance guardrails.

What you will do

• Design, train, and ship speech-to-speech and real-time voice models that improve latency, turn-taking, naturalness, robustness, and interruption handling on live calls.
• Build and improve the production speech stack, including neural codecs, streaming inference, ASR/TTS or speech-to-speech pathways, turn detection, and speech enhancement.
• Develop evaluations, harnesses, and monitoring based on real borrower conversations rather than clean benchmarks.
• Diagnose telephony noise, barge-in, accent and channel variation, and overlapping-speech failures, then convert them into model, data, or systems improvements.
• Work across models, data, infrastructure, and product with the Applied AI and Voice AI teams to improve end-to-end agent quality.
• Own major technical areas from problem definition through production deployment with significant autonomy.

Requirements

• 5+ years of experience in speech, audio, or related machine learning, or equivalent demonstrated depth through shipped systems and public work.
• Proven experience with speech-to-speech, full-duplex, or other real-time conversational speech systems; offline ASR or TTS alone is not sufficient.
• Public proof of work such as papers, GitHub repositories, Hugging Face models or datasets, or other inspectable artifacts.
• Strong engineering fundamentals and ability to build reliable production systems, including streaming or low-latency inference.
• Ability to diagnose messy real-world model failures and turn them into practical improvements.
• High ownership, strong execution speed, and comfort operating in ambiguous technical areas.

Nice to have

• Deep experience with neural audio codecs, vocoders, or discrete speech representations used in modern speech-to-speech stacks.
• Experience with turn detection, barge-in, speech enhancement, or multilingual speech in production telephony or contact-center settings.
• Experience post-training or adapting language models for voice agents and building evaluations that predict production quality.
• Familiarity with regulated or high-stakes conversations where errors have real consequences.

Culture & Benefits

• Fully remote role with close collaboration with the Applied AI team at the San Francisco headquarters.
• High-ownership work on a small, high-caliber Applied AI team with fast sprints and major launches.
• Work affects millions of live conversations and covers the full production voice AI stack.
• Full-time employees receive medical, dental, and vision coverage, a 401(k), and catered lunches; benefits are confirmed for the country of hire.
• The team typically works around 60 hours per week, beginning at 8:00 AM, with four in-person collaboration days in San Francisco.