Member of Technical Staff – ML Engineer

Rad Hires; New York (NY); On-site; USD 150,000 - 300,000; Full time

Benefits offered by this job

Comprehensive health, dental, and vision benefits

Visa sponsorship available

Opportunity to work with world-class colleagues

Job summary

A fast-growing AI startup in New York City is seeking a Member of Technical Staff in ML Engineering. In this role, you'll design and build complex systems for AI agents, collaborating with top engineers in the field. Ideal candidates have 4-8 years of experience, a strong foundation in Machine Learning, and a passion for solving complex problems in a dynamic startup environment. Compensation is competitive, ranging from $150K to $300K, with extensive benefits and equity opportunities.

Qualifications

• 4–8 years of experience building complex systems (Python preferred).
• Strong background in Machine Learning fundamentals.
• Experience as an early technical member at a fast-paced startup.

Responsibilities

• Design and build the 'world' for AI agents.
• Develop frameworks for AI agents to navigate workflows.
• Take ownership of projects from design to deployment.

Skills

Python

Machine Learning fundamentals

Complex system modeling

Interconnected systems reasoning

Education

Degree in Computer Science, Physics, Math, or Statistics

Job description

Member of Technical Staff – ML Engineering

Note: This role is 100% on-site in NYC

About the Company

This fast-growing NYC-based AI startup is revolutionizing the accounting industry by building a team of AI agents that execute real-world accounting workflows. Founded in 2023 and headquartered in the Flatiron district, the company has already:

• Raised $34M from top-tier investors including leaders from the ML and fintech sectors.
• Achieved product‑market fit with demand exceeding current capacity.
• Experienced 10x revenue growth in just the past 5 months.

They operate on the cutting edge of what’s technically possible, assembling top minds from ML, engineering, and accounting. Joining now means becoming an early member of a small, high‑ownership team shaping the future of AI in enterprise systems.

What You’ll Do

As a Member of Technical Staff on the World Modeling team, you will:

• Design and build the “world” that the company’s AI agents interact with, modeling interconnected systems and abstractions.
• Develop frameworks and coding structures that enable AI agents to understand and navigate complex real‑world workflows (e.g., accounting tasks).
• Define rules, constraints, and context in which AI agents operate.
• Collaborate with top engineers, ML researchers, and domain experts in an interdisciplinary team.
• Take ownership of projects end-to-end, from design to production deployment.
• Mentor and be mentored by other engineers as the team scales rapidly.

Role Requirements

Experience & Skills

• 4–8 years of experience building complex systems (Python preferred).
• Strong background in Machine Learning fundamentals, with a first‑principles mindset.
• Deep experience modeling interconnected systems and reasoning about trade‑offs and constraints.
• Previous experience as an early technical member at a fast‑paced startup.
• Degree in Computer Science, Physics, Math, or Statistics (preferably from a top university).

Attributes

• Intense curiosity and drive to solve hard, complex problems.
• Thrives in a high‑ownership, high‑speed startup environment.
• Eager to work in‑person 5 days/week with a cross‑disciplinary team.
• Dedicated to mentoring and collaboration.

Compensation & Benefits

• Base Salary: $150K – $300K
• Equity: Highly competitive, well above market
• Comprehensive health, dental, and vision benefits
• Visa sponsorship available (all types)
• Opportunity to build on the cutting edge of AI alongside world‑class colleagues

Tech Stack

• Languages: Python (primary), with potential for other languages as needed
• Focus Areas: Machine Learning, agentic systems, large‑scale system modeling, data infrastructure

Interview Process

1. Intro Call
2. Initial Screen
3. Technical Interview 1
4. Technical Interview 2
5. Onsite Interview (3–4 hours)
6. Offer
7. Hiring

Number of Vacancies

5 positions available