Senior Machine Learning Engineer

Kadence Inc.
Los Altos, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 325K

Job location

Los Altos, United States of America

Tech stack

Continuous Delivery
Python
Machine Learning
PyTorch
Large Language Models
Machine Learning Operations

Job description

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.

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., * 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., * ML Engineer with Real-World Experience - You've trained and shipped models in production. Bonus if you've worked with LLMs or audio models.

Requirements

  • 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.

Benefits & conditions

  • $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.

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