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Senior Member of Technical Staff, Applied ML

$175k - $300k
Full-time

True Talent Solutions Partners

About the Role

Own end-to-end applied machine learning projects for an AI-powered accounting platform. You will build agent systems that automate complex financial workflows, combining research-minded experimentation with practical engineering to deliver reliable systems at scale.

What You'll Do

  • Design and iterate on multi-agent architectures, including safety boundaries and fallback behaviors.

  • Manage agent context, memory, and loops, and optimize model routing against measurable success criteria.

  • Build scalable offline and online evaluation pipelines that automate experiments, metrics, and labeling strategies.

  • Instrument systems to identify regressions, track error patterns, and support continuous improvement.

  • Develop prompt and retrieval pipelines, and transform messy documents into structured representations for reasoning.

  • Build guardrails and validation layers, and test and communicate progress on end-to-end systems.

What We're Looking For

  • 4 to 12 years of applied machine learning engineering experience, with deep expertise in Python and LLM or transformer-based systems.

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

  • A track record designing multi-agent systems and retrieval pipelines, and running structured experiments that use hypotheses and measurable results.

  • Experience at a fast-paced startup is essential; backgrounds in quant or hedge funds or leading technology companies are also relevant.

  • Strong computer science fundamentals and a technical background in computer science, math, physics, or a related field.

  • Clear communication skills and enthusiasm for applying AI to accounting, finance, and the broader economy.

Compensation & Benefits

Base salary: $175,000 to $300,000 USD annually. Visa sponsorship is available.

Location

On-site, five days per week in New York, NY. Candidates should be based in the United States or Canada, ideally on the East Coast.

Vacancy posted 2 days ago
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