Applied AI Scientist

Balyasny Asset Management

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$150,000–$225,000 / yr
Posted
18 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $222k
This role $188k
$135k most similar roles pay here $293k

This role pays less than 74% of similar roles. Most pay $186,025–$257,212 — the shaded band above. At the midpoint, this role pays about $188k versus about $222k for comparable roles.

Based on 240 similar postings.

Employer

About Balyasny Asset Management

Balyasny Asset Management (BAM) is a global multi-manager hedge fund offering diversified investment strategies across equities, macro, commodities, and systematic trading.

Balyasny Asset Management currently has 59 open roles on FindRole.

Listed pay typically runs $175,000–$250,000 across 30 roles with salary data.

Most-posted roles

View all roles at Balyasny Asset Management

At a glance

TL;DR · Applied AI Scientist

As an Applied AI Scientist – AI Fellowship Program, you will join a rotational program where you are embedded with the central AI team before transitioning to investment teams as a dedicated partner to portfolio managers. You will build production tooling, agentic workflows, data pipelines, and research automation designed to improve decision speed and automate research processes. The role requires translating ambiguous requirements from non-technical stakeholders into technical solutions while tracking emerging LLM techniques and agentic frameworks. Key technical requirements include proficiency in Python for engineering and statistical modeling, experience with model provider APIs like OpenAI, Anthropic, and Google, and familiarity with LangGraph or the OpenAI Agents SDK. You will also utilize tools such as Claude Code, Codex, and MCP to solve complex problems within an investment setting.

What you'll do

  • Design, build, and deploy agentic workflows and data pipelines to improve portfolio manager decision speed.
  • Develop research automation and screening tools tailored to live investment problems.
  • Contribute production tooling to the company's central AI ecosystem and platform.
  • Translate ambiguous requirements from non-technical stakeholders into functional technical solutions.
  • Track emerging LLM techniques and agentic frameworks to pilot new technologies on real investment problems.
  • Integrate LLMs and AI models into production workflows using various provider APIs and agentic frameworks.

What we're looking for

  • Master's degree in AI, Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field (advanced degrees preferred).
  • Strong grounding in computer science, statistics, machine learning, and generative AI.
  • 3 to 5 years of experience in a user-facing role building and deploying LLM-based solutions in production.
  • Demonstrable experience building LLM-based applications using agentic frameworks.
  • Experience working with non-technical stakeholders to shape and deliver technical solutions.
  • High proficiency in Python for engineering, statistical modeling, and machine learning.
  • Familiarity with model provider APIs, agentic frameworks (LangGraph, OpenAI Agents SDK, Claude Agent SDK), and coding tools like Claude Code or Codex.
  • Exposure to buy-side, equity research, or other investment settings (preferred).

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