Applied AI Scientist

Balyasny Asset Management

Confirmed live today High trust

Quick summary

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

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $216k
This role $188k
$135k $287k
below market most similar roles pay here above market

This role pays less than 68% of similar roles. Most pay $177,250–$254,750 — the blue band above. At the midpoint, this role pays about $188k versus about $216k 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 53 open roles on FindRole.

Listed pay typically runs $175,000–$250,000 across 37 roles with salary data.

Most-posted roles

View all roles at Balyasny Asset Management

At a glance

TL;DR · Applied AI Scientist

The Applied AI Scientist – AI Fellowship Program is a rotational role where you will join the central AI team before embedding with various investment teams as a dedicated AI partner. You will design, build, and deploy agentic workflows, data pipelines, and research automation to improve portfolio managers' decision speed and research processes. Your daily work involves translating ambiguous investment requirements into technical solutions and tracking emerging LLM techniques. You must be proficient in Python for engineering and statistical modeling, with experience integrating LLMs into production workflows using APIs from OpenAI, Anthropic, and Google. Required skills include agentic frameworks like LangGraph, coding tools like Claude Code, and MCP for data integration. This role solves complex investment problems by automating equity research and screening tools.

What you'll do

  • Design, build, and deploy agentic workflows and data pipelines to improve portfolio manager research processes.
  • Develop research automation and screening tools to increase investment decision speed.
  • Master the in-house AI ecosystem while contributing production tooling to the central platform.
  • Translate ambiguous investment workflows and requirements into working technical solutions for PMs and analysts.
  • Track emerging LLM techniques and pilot promising agentic frameworks on real investment problems.
  • Integrate LLMs and AI models into production workflows using Python and various model provider APIs.
  • Manage multiple workstreams to deliver technical solutions on deadline.

What we're looking for

  • Master's degree in AI, Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent work experience.
  • Advanced degrees are preferred.
  • Strong grounding in computer science, statistics, machine learning, and generative AI.
  • 3–5 years of experience in a user-facing role scoping, building, and deploying LLM-based solutions in production.
  • Demonstrable experience building LLM-based applications using agentic frameworks.
  • Highly proficient in Python for engineering, statistical modeling, and machine learning.
  • Experience integrating LLMs and AI models into production workflows.
  • Familiarity with model provider APIs, agentic frameworks, cloud platforms, Git, and workflow orchestration tools like Airflow (preferred).

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