Founding Machine Learning Engineer

This is a first machine learning hire who will own the models and agents that carry out billing work, along with the evaluation and data pipelines that support them, and will set the technical direction for all of it. A strong candidate brings many years of hands on ML system building and has put language model or agent systems into production where real users rely on them.

That person also knows how to design evaluations, judge when fine tuning is the right call, and keep cost and latency under control in live systems.

The core of the job is building AI that does billing tasks, so the work sits directly in the shift toward automated back office operations. The human side stays in judgment: choosing what to build, defining how quality is measured, and deciding when a model needs tuning versus other fixes. Production discipline around cost and speed remains a person's responsibility even as the models do more of the task work.

Someone here would gain deep experience running language model and agent systems in a regulated, detail heavy domain, from evaluation design through production cost and latency tradeoffs. Building that background means shipping agent workflows that real users depend on and learning to measure their reliability carefully. Familiarity with healthcare data would help but is not required to start.

• Shipped LLM agent systems
• Production ML ownership
• Fine tuning judgment
• Cost and latency control

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

Taiga provides AI-native medical billing for independent practices, handling coding, claims, and appeals end-to-end (per the company).