Senior Machine Learning Engineer

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.

Qualifications

• 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.

Compensation

Cash: $225,000 - $325,000 base salary
Equity: Offers Equity