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Founding ML Engineer (SF hybrid/onsite)

Cadre
Full-time
On-site
San Francisco, California, United States

🚀 Founding Machine Learning Engineer

Location: San Francisco, CA (Onsite preferred, Remote considered for exceptional candidates)
Type: Full-time
Visa Sponsorship: Available for candidates already based in the U.S.
Compensation: Competitive salary + 0.5%–2% equity
Start Date: ASAP

đź§  About Outspeed

Outspeed powers emotionally intelligent voice companions and agents with emotion and memory—redefining the way humans interact with machines through real-time, expressive, and persistent voice interfaces.

We’re solving some of the toughest problems in machine learning and systems engineering—from low-latency inference and scaling, to multi-user conversational memory and emotion modeling. If you’re excited by the frontier of conversational AI, you’ll be at home here.

Founded in 2024 and based in San Francisco, we're a tight-knit team of 4 building at the intersection of speech, emotion, and intelligence.

Learn more: outspeed.com

🎯 What You'll Do

  • Own and scale key ML systems: speech models, memory, emotional synthesis, real-time transformers

  • Optimize inference latency and throughput for streaming models

  • Architect data pipelines for fine-tuning and continual learning

  • Collaborate across voice UX, product, and backend infra to ship intelligent, responsive agents

  • Push the limits of what's possible in conversational AI—from prototype to production

đź§© You Might Be a Fit If You Have:

  • 2–7 years of experience as an ML engineer, especially in real-time ML systems (voice, video, or interactive apps)

  • Hands-on fluency with PyTorch, CUDA, and pre-trained transformer models

  • Proven experience optimizing streaming model inference performance

  • Experience with voice interfaces or emotion-aware synthesis (bonus for Bark, Tortoise, etc.)

  • Strong data engineering instincts—architecting + processing pipelines

  • Familiarity with tools like VLLM, SGLang, or similar inference engines

  • Deep interest in expressive AI, latency-sensitive systems, and emotional computing

  • A degree in CS or related field from a top-tier university (preferred)

🌱 Bonus Points For:

  • Prior experience at AI-native companies like Runway ML, Descript, AnyScale, DeepMind, etc.

  • Open-source contributions (share your GitHub!)

  • Previous startup/founding experience or hunger for 0→1 building

  • Passion for real-time voice UX, multi-modal agents, and persistent memory architectures

⚠️ What We're Not Looking For:

  • 15–20 year veterans with unclear startup intent or urgency

  • Big tech lifers (e.g. 7+ years at FAANG with no startup exposure)

  • Candidates with certification-heavy resumes and minimal build experience

  • Anyone not ready to start within 1 month

🌍 Work Culture & Expectations

  • Location: Preferably SF-based or open to relocating. Remote is OK for exceptional global candidates.

  • Pace: Expect ~60 hour weeks. We value high energy and deep focus, with flexibility when it matters.

  • Team: Tiny but mighty. You’ll be the 5th team member.