Member of Technical Staff, Applied ML

About the Role

Join an applied machine learning team building AI systems for accounting and finance workflows. You will own projects end to end, from defining success and running experiments to shipping reliable agent systems that can reason, plan, and evaluate their performance.

What You'll Do

• Design and evolve multi-agent systems that automate complex accounting workflows.

• Define agent autonomy boundaries, tool use, fallback behaviors, and validation layers to support safe and reliable operation.

• Build context and memory systems, retrieval and indexing pipelines, and document-processing workflows.

• Route and optimize models for latency, cost, and accuracy under real-world constraints.

• Create scalable offline and online evaluation pipelines, define benchmarks and metrics, and use results to guide product and architecture decisions.

• Instrument systems to track errors, detect regressions, and support continuous improvement.

• Scope projects, write clear technical specifications, build and test systems end to end, and communicate progress and findings.

What We're Looking For

• Four to twelve years of machine learning engineering experience, including industry work applying machine learning fundamentals.

• Experience building end-to-end LLM-based agent applications, including model orchestration, benchmarking, and evaluation of agent behavior and reliability.

• Deep expertise in Python and LLM or transformer-based systems; experience with Postgres is relevant.

• Experience designing structured ML experiments, evaluation infrastructure, and measurable iteration cycles.

• Background building machine learning products in a fast-paced startup, quantitative finance, or similarly demanding environment.

• Strong technical fundamentals, clear communication, and the ability to explain complex concepts simply.

• Interest in AI's impact on accounting, finance, and the broader economy.

Compensation & Benefits

Base salary: $175,000 to $350,000 USD annually. Visa sponsorship is available.

Location

On-site in New York, NY, with a five-day-per-week office schedule.