Member of Technical Staff - Applied ML

Company: Confidential - Series B AI accounting company
Location: New York, NY (Flatiron office, in person 5 days per week)
Compensation: $175,000 - $350,000 + highly competitive equity
Employment Type: Full-time
Visa Sponsorship: Visa transfers; can sponsor all types

About the Company

A Series B AI company building agents that do real accounting and finance work end to end, used daily by accountants for complex tasks, with capabilities improving every month.

The Role

As an ML Engineer at the company, you will own end-to-end projects that bring intelligence into production: the systems that help its agents reason, plan and evaluate themselves. You will have full autonomy to plan projects, define success, run experiments and decide when a system is ready to ship. This is an applied role for engineers who want to operate as researchers and builders at once.

What You Will Do

• Design and iterate multi-agent architectures that automate real accounting workflows, with clear autonomy boundaries, tool usage and fallback behavior.
• Manage context and memory across agent steps; route, evaluate and optimize models under latency, cost and accuracy constraints.
• Build scalable offline and online evaluation pipelines that run hundreds of experiments automatically, with golden tasks, labeling strategies and metrics.
• Instrument the stack to catch regressions, track error taxonomies and drive closed-loop improvement.
• Architect prompt stacks, retrieval and indexing pipelines, and document parsing into structured representations agents can reason about.
• Scope projects with concise specs, build and test end to end, and communicate progress clearly within your pod.

What You Bring

• 4-12 years as a machine learning engineer
• Experience at a fast-paced startup (Series A-D), a tier-1 tech company or a hedge fund
• End-to-end LLM agent applications: benchmarking, model orchestration and evals for agent behavior and reliability
• Structured ML experimentation: framing hypotheses, building evaluation infrastructure, iterating on measurable results
• CS, physics, math or other technical degree from a top school
• Very clear communication
• Located in the US or Canada and able to work in the New York office 5 days a week

Nice to Have

• ML products and underlying models at a fast-paced company
• Deep Python and LLM/transformer expertise
• Interest in AI's impact on accounting and finance

Interview Process

Initial screen with leadership, meet-the-team screen, technical coding interview, onsite plus references.

Tech Stack

Python, Postgres, LLMs, agent frameworks, evaluation pipelines