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 together.

• We’re a top 50 AI app in a16z list: https://tinyurl.com/5853dt2x
• #4 on Brex's Fast-Growing Software Vendors of 2025: https://www.brex.com/journal/brex-benchmark-december-2025
• 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: $215,000 - $290,000 base salary
• Equity: Offers Equity
• 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 (15min): 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): LLM theory specific coding Interview(Pytorch)

• 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 whiteboarding 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.