Member of Technical Staff - ML & Agent Design (Staff)

Recruiting From Scratch; New York (NY); Remote; USD 100,000 - 300,000; Full time

Job summary

A leading talent firm seeks a leader for their Agent Design group to build advanced agents that automate workflows. This unique role requires collaboration with the ML research team and expertise in cutting-edge technologies like LLMs and reinforcement learning, aimed at addressing complex tasks in accounting and automation.

Qualifications

• Strong interest or experience in ML, agent architectures, and optimization problems.
• Ability to integrate advanced ML techniques into projects.

Responsibilities

• Design, build, and refine agents for complex workflows.
• Prototype and test system architectures for challenging tasks.
• Develop ML strategies to solve optimization problems.

Skills

Large Language Models (LLMs)

Agent Architectures

Information Theory

Reinforcement Learning (RL)

Job description

Who is Recruiting from Scratch:

Recruiting from Scratch is a talent firm that focuses on placing the best candidate for our clients. Our team is 100% remote and we work with teams across North America, South America, and Europe to help them hire.

https://www.recruitingfromscratch.com/

Salary Range: $100,000-$300,000 base.

About the Role
A dynamic and innovative team is seeking a leader for their Agent Design group, focused on building advanced systems of agents that autonomously complete end-to-end workflows. In this role, you’ll collaborate closely with the machine learning research team to integrate the latest advancements, run cutting-edge experiments, and bring innovative ideas to life.

The ideal candidate has experience or a strong interest in areas such as large language models (LLMs), agent architectures, information theory, and reinforcement learning (RL).

Responsibilities

• Agent Development: Design, build, and refine agents capable of executing complex workflows, specifically within accounting and related domains.
• Architectural Prototyping: Prototype and test different system architectures to tackle increasingly challenging tasks effectively.
• ML-Driven Optimization: Develop machine learning strategies to address optimization problems, leveraging state-of-the-art techniques.

This is a unique opportunity to lead impactful projects at the intersection of agent design, ML research, and workflow automation.