Senior Machine Learning Engineer

Retell AI; San Francisco (CA); On-site; USD 200,000 - 280,000; Full time

Benefits offered by this job

100% medical, dental, and vision insurance

$70/day DoorDash credit

$200/month wellness reimbursement

$300/month commuter reimbursement

$75/month phone bill reimbursement

$50/month internet reimbursement

Job summary

A leading voice AI startup is seeking a Founding Senior Machine Learning Engineer to fine-tune and deploy human-like voice agents, handling millions of real-time calls. This role offers a salary range of $200,000 to $280,000 per year, with significant equity and benefits including full medical coverage and daily meal allowances. Candidates should have real-world experience in deploying ML models and work well in a fast-paced environment.

Qualifications

• Experience with ML models, especially LLMs or audio models.
• Proficient in modern ML tools.
• Strong communication skills.

Responsibilities

• Fine-tune LLMs and audio models for production.
• Build datasets and metrics for evaluating model performance.
• Deploy models ensuring reliability and speed.
• Collect structured human feedback for model improvements.
• Design ML infrastructure for efficient experimentation.

Skills

Training and shipping models in production

Fluent in Python and PyTorch

Team collaboration

Execution-oriented

Adaptable and resilient

Job description

Founding Senior Machine Learning Engineer

Join to apply for the Founding Senior Machine Learning Engineer role at Retell AI.

Base pay range

$200,000 – $280,000 per year

About Retell AI

Retell AI is using first principles to reimagine the call center with cutting‑edge voice AI. We believe voice is still the most natural way humans communicate, yet it has been trapped in outdated call centers for decades. Our mission is to bring intelligence, empathy, and speed to every phone conversation between businesses and their customers.

Since launching 18 months ago, thousands of companies now use Retell’s AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Altman Capital, and other leading investors, we have scaled to $30M ARR with a team of 20 people, up from $5M at the start of 2025.

Now, we’re scaling fast, and we’re looking for bold, ambitious people to help us build the gold standard for voice automation. If you want to work on deeply technical challenges, move fast, and make an outsized impact at one of the fastest‑growing Voice AI startups in the world, you’ll love it here.

Let’s build the future of voice automation together.

• We’re a top 50 AI app in a16z list: https://tinyurl.com/5853dt2x
• We're also one of the top ranking startups on: https://leanaileaderboard.com/

About the Role

This is a hands‑on, high‑ownership role for ML engineers who want to build production models that actually ship and perform under real‑world constraints. As a Founding Senior Machine Learning Engineer at Retell, you’ll work across the ML stack to power human‑like voice agents that handle millions of real‑time phone conversations. You’ll fine‑tune large language models and audio models, evaluate them with rigorous benchmarks (and human feedback), and deploy them into latency‑sensitive, high‑traffic systems. You’ll own model performance end‑to‑end—from training pipelines to post‑deployment monitoring—and shape our ML strategy alongside the founding team. If you’re excited by hard technical challenges, fast iteration, and the opportunity to define how voice AI works at scale, this role is a rare chance to do it from the ground up.

Key Responsibilities

• Train & Tune Models – Fine‑tune LLMs and audio models to maximize speed, accuracy, and production‑readiness—pushing the frontier of real‑time AI voice experiences.
• Benchmark & Evaluate – Build datasets, define rigorous metrics, and measure model performance across high‑impact voice AI tasks to guide development.
• Deploy to Production – Work closely with engineering to ship models, monitor them in the wild, and ensure they stay fast, reliable, and accurate at scale.
• Run Human Evaluations – Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations.
• Level Up Infrastructure – Design and maintain the ML infrastructure needed for fast experimentation, robust training, and continuous deployment.

YOU MIGHT THRIVE IF YOU

• ML Engineer with Real‑World Experience – You’ve trained and shipped models in production. Bonus if you’ve worked with LLMs or audio models.
• Fluent in Modern ML Stack – You know your way around Python, PyTorch, and today’s ML tools—from training pipelines to evaluation benchmarks.
• Execution‑Oriented – You move fast, take ownership, and focus on solving real problems over perfect ones.
• Startup‑Ready – You’re adaptable, resilient, and energized by ambiguity and fast‑changing priorities.
• Clear Communicator & Team Player – You collaborate well across functions and push decisions forward.

JOB DETAILS

• Cash: $200,000 – $280,000 base salary
• Equity: 0.15% – 0.35%
• Location: Redwood City, CA, US
• US Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 visas.

Other Benefits

• 100% coverage for medical, dental, and vision insurance
• $70/day DoorDash credit for unlimited breakfast, lunch, dinner, and snacks
• $200/month wellness reimbursement (gym, fitness classes, etc.)
• $300/month commuter reimbursement (gas, Caltrain, etc.)
• $75/month phone bill reimbursement
• $50/month internet reimbursement

Compensation Philosophy

• Best Offer Upfront: Choose from three cash‑equity balance options, no negotiation needed.
• Top 1% Talent: Above‑market pay (top 5 percentile) to attract high performers.
• High Ownership: Small teams, >$1M revenue/employee, and significant equity.
• Performance‑Based: Offers tied to interview performance, not experience or past salaries.

INTERVIEW PROCESS

• Online Assessment (30 min): Coding questions on practical problem‑solving (7 days to complete).
• Talent Screen (15 min): Chat with our recruiter to get a better sense of the role, the team, and what it’s like to work here.
• Technical Interview (45 min): Machine Learning specific coding interview.
• Technical Interview (45 min): Live Practical Systems Design and Coding interview.
• Onsite/Virtual Interviews (3 hrs): Hosted in our office if located in the Bay Area or virtual, with three rounds:
  • ML System Design: A non‑coding interview focused on white‑boarding and high‑level system architecture.
  • ML Question Deep Dive: In‑depth discussion exploring your approach to a machine learning problem.
  • Backend + AI Practical: A hands‑on coding interview combining backend development with AI integration.
  • Offer: Final stage, pending decision and offer discussion.