Member of Technical Staff, Applied ML

True Talent Solutions Partners; New York (NY); On-site; USD 175,000 - 350,000; Full time

Benefits offered by this job

Visa sponsorship available

Job summary

True Talent Solutions Partners is seeking an experienced ML engineer to lead end-to-end development of production AI agents for accounting and financial workflows. You will define success, run experiments, and ship reliable systems that enable agents to reason, plan, and evaluate their work.

The role emphasizes strong Python skills, transformer-based ML, and building end-to-end agent applications, with a focus on performance, latency, and cost optimization within a fast-paced startup/finance

Qualifications

• Four to twelve years of machine learning engineering experience, including applied ML work in industry.
• Strong Python skills and deep familiarity with LLM and transformer-based systems.
• Experience delivering end-to-end LLM agent applications, including model orchestration, benchmarking, and evaluation of agent behavior and reliability.
• Experience framing structured ML experiments, building evaluation infrastructure, and iterating based on measurable results.
• Background in a fast-paced startup, quantitative finance, or a high-caliber technology environment, with experience building ML products and underlying models.
• Strong technical fundamentals in computer science, physics, mathematics, or a related field, plus clear communication and an ability to explain complex ideas simply.
• Interest in applying AI to accounting, finance, and related workflows.

Responsibilities

• Own projects end to end from defining success and experiments to shipping reliable systems.
• Design and improve multi-agent architectures for automated workflows.
• Build agent loops and memory systems supporting coherent task execution.
• Route, evaluate, and optimize models for latency, cost, and accuracy.
• Create automated evaluation pipelines, define metrics and benchmarks to guide decisions.
• Instrument systems to detect regressions and support continuous improvement.
• Develop prompt and retrieval systems, parsing pipelines, and validation layers for safe behavior.
• Scope projects, write technical plans, build and test systems end to end, and share progress with teammates.

Skills

Python

LLM/Transformers

End-to-end ML apps

Experiment design

Finance domain experience

CS/Math fundamentals

Communication

Job description

About the Role

Join an applied machine learning team building production AI agents for accounting and financial workflows. You will own projects end to end, from defining success and running experiments to shipping reliable systems that help agents reason, plan, and evaluate their work.

What You'll Do

• Design and improve multi-agent architectures that automate real-world workflows, with clear autonomy boundaries, tool use, and fallback behaviors.

• Build agent loops and context and memory systems that support coherent, measurable task execution.

• Route, evaluate, and optimize models for latency, cost, and accuracy.

• Create automated offline and online evaluation pipelines, define metrics and benchmark tasks, and use results to guide product and architecture decisions.

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

• Develop prompt and retrieval systems, document parsing pipelines, and validation layers for safe, reliable behavior.

• Scope projects, write concise technical plans, build and test systems end to end, and share progress and learnings with teammates.

What We're Looking For

• Four to twelve years of machine learning engineering experience, including applied ML work in industry.

• Strong Python skills and deep familiarity with LLM and transformer-based systems.

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

• Experience framing structured ML experiments, building evaluation infrastructure, and iterating based on measurable results.

• Background in a fast-paced startup, quantitative finance, or a high-caliber technology environment, with experience building ML products and underlying models.

• Strong technical fundamentals in computer science, physics, mathematics, or a related field, plus clear communication and an ability to explain complex ideas simply.

• Interest in applying AI to accounting, finance, and related workflows.

Compensation & Benefits

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

Location

On-site in New York, NY.