Lead Data Scientist - Advanced AI Systems Development

Aquent • United State
Remote
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AI Summary

Lead the development of advanced AI systems, designing and implementing sophisticated goal-setting and decomposition mechanisms, dynamic planning systems, and intelligent agents. Ensure AI agents are reliable, interpretable, and robust. Use technical expertise to drive collaborative innovation.

Key Highlights
Lead AI systems development
AI agent reliability and interpretability
Technical expertise in AI engineering
Key Responsibilities
Design and implement sophisticated goal-setting and decomposition mechanisms for autonomous agents
Develop robust evaluation frameworks to ensure agent alignment with human intent
Prototype intelligent agents capable of interfacing seamlessly with various systems
Technical Skills Required
SQL Python Pytorch Jax LangChain LangGraph AutoGen SQL Advanced data analysis/data mining tools
Benefits & Perks
Fully remote work
Subsidized health, vision, and dental plans
Paid sick leave
Retirement plans with a match
Nice to Have
Ph.D. in Computer Science, Data Science, Machine Learning, or a closely related quantitative field
Experience with Large Language Model (LLM)-based agents
Direct experience with advanced simulations

Job Description


Lead Data Scientist

Location: Fully remote; however, ideally, you will work a hybrid work style in one of the following six locations: Louisville, KY; Boston, MA; New York, NY; Washington DC; Tampa, FL; Dallas, TX

Aquent is partnered with a pioneering enterprise AI organization dedicated to driving innovation across critical business segments. This team collaborates with world-leading experts to deliver cutting-edge AI technologies, significantly improving care quality and the experience for millions of consumers. Be part of shaping the future of healthcare through AI excellence, contributing to groundbreaking advancements that truly make a difference.

We are seeking a visionary leader to spearhead the development of advanced agentic systems, capable of autonomously managing and decomposing complex goals. In this pivotal role, you will be instrumental in designing, planning, and controlling intelligent agents that can set, adapt, and execute objectives in dynamic, real-world environments. Your expertise will directly contribute to the scientific and engineering foundations that ensure AI agents are reliable, interpretable, and robust across long-horizon tasks, making a tangible impact on the lives of millions.

What You’ll Do

  • Architect sophisticated goal-setting and decomposition mechanisms for autonomous agents navigating uncertain or open-ended environments.
  • Design and implement cutting-edge dynamic planning systems, including hierarchical planning, curriculum learning, and self-refinement loops.
  • Drive collaboration on memory, tool-use, and feedback-loop designs to enable complex, multi-step, and self-directed agent behaviors.
  • Develop robust evaluation frameworks to ensure agent alignment with human intent, consistency, and progress towards long-horizon objectives.
  • Prototype intelligent agents capable of interfacing seamlessly with various systems (e.g., APIs, enterprise servers, search engines, databases, real-world actuators) to pursue goals safely and efficiently.
  • Innovate mechanisms to proactively detect and mitigate goal misalignment, looping behaviors, or undesirable emergent strategies in AI systems.
  • Partner with cross-functional teams to integrate goal alignment with critical safety, ethical alignment, and operational reliability mechanisms.

Must-Have Qualifications

  • Master’s Degree combined with 4+ years of experience in research/ML engineering or an applied research scientist role, ideally focused on production-ready AI solutions.
  • 2+ years of demonstrated leadership experience in the development of AI/ML systems.
  • Expert proficiency in SQL, Python, and advanced data analysis/data mining tools.
  • Hands-on experience with leading machine learning frameworks such as Pytorch, Jax, LangChain, LangGraph, or AutoGen.
  • Proven track record with high-performance, large-scale ML systems.
  • Deep experience in language modeling, particularly with transformer architectures.
  • Solid understanding and experience with symbolic planning, causal reasoning, and model-based reinforcement learning.
  • Expertise in large-scale ETL processes.

Nice-to-Have Qualifications

  • Ph.D. in Computer Science, Data Science, Machine Learning, or a closely related quantitative field.
  • Demonstrated experience successfully deploying autonomous or semi-autonomous agents in production environments or advanced simulations.
  • Direct experience with Large Language Model (LLM)-based agents, including techniques like scratchpad/self-reflection or hierarchical task decomposition.
  • A strong understanding of autonomy risk mitigation strategies, such as off-switch protocols or bounded rationality principles.

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About Aquent Talent

Aquent Talent connects the best talent in marketing, creative, and design with the world’s biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. More information on our awesome benefits!

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We’re about creating an inclusive environment—one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.


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