This role involves building production models that ship and perform under real-world constraints. As a Founding Senior Machine Learning Engineer, you'll work across the ML stack to power human-like voice agents. You'll fine-tune large language models and audio models, evaluate them with rigorous benchmarks, and deploy them into latency-sensitive, high-traffic systems.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Senior Machine Learning Engineer
Location: San Francisco Bay Area
Employment Type: Full-time
Location Type: On-site
Compensation: Base Salary $225K – $325K • Offers Equity
My client is using the first principles to reimagine the call center with cutting-edge voice AI.
Since launching, thousands of companies now utilize their voice agents to handle sales, support, and logistics calls that once required large teams of human agents.
They're growing quickly and looking for ambitious builders who want to tackle hard technical problems, move fast, and have real impact at one of the fastest-growing voice AI startups.
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, 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.
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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 ARE
• A 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.
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JOB DETAILS
• US Visas: My client 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
• $300/month commuter reimbursement
• $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.
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