Research Scientist - Agents (Post Training)

Mohamed bin Zayed University of Artificial Intelligence; Sunnyvale (CA); On-site; USD 150,000 - 450,000; Full time

Benefits offered by this job

Medical, dental and vision benefits

Bonus

401K Plan

Generous paid time off, sick leave and

Holidays

Paid Parental Leave

Employee Assistance Program

Life insurance and disability

Job summary

Mohamed bin Zayed University of Artificial Intelligence seeks researchers and engineers to tackle challenges in training advanced agentic language models that reason and use tools to complete tasks on a computer. You will build high-quality training datasets, robust evaluations, and reinforcement learning infrastructure.

The role spans research and systems across algorithms, empirical work, and optimization.

Qualifications

• 2 years of experience in LLM training, fine-tuning, evaluations, or distributed ML.
• Python and PyTorch development experience.
• Experience using LLM agents for SWE tasks.
• Experience in designing and implementing algorithms from scratch.
• Experience in dataset curation and generation.
• Experience in building or contributing to training/serving infrastructure.
• Experience in designing and deep diving into evaluations.

Responsibilities

• Propose, prototype, and scale algorithms/systems to support agentic learning.
• Develop new paradigms for agentic behavior that go beyond current practices.
• Contribute to technical reports, research publications, and open‑source software.
• Collaborate with other teams to produce state‑of‑the‑art foundation models.

Skills

Python

PyTorch

LLM agents experience

Algorithm design

Distributed ML

Dataset curation

LLM inference

Reinforcement learning

Education

BS, MS, or PhD in Computer Science, Machine Learning

Tools

Ray

Triton

CUDA C++

Job description

About the Institute of Foundation Models

We are a dedicated research lab for building, understanding, using,and risk-managing foundation models. Our mandate is to advanced research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.

Position Summary

As a member of the Agents team, you will tackle research and engineering challenges to train advanced agentic language models that are adept at using reasoning and tool use to complete tasks on a computer. These challenges range from building high-quality training datasets and robust evaluations to innovative reinforcement learning infrastructure, algorithms and environments. The team aims to recruit candidates across the research-engineering spectrum, from algorithmic and empirical research to large-scale systems and optimization, reflecting the breadth of interesting problems we aim to solve. We value depth in any subset of these areas; there is no single “right” background.

Key Responsibilities

• Propose, prototype, and scale algorithms/systems to support agentic learning
• Develop new paradigms for agentic behavior that go beyond current practices
• Contribute to technical reports, research publications, and open‑source software
• Collaborate with other teams to produce state‑of‑the‑art foundation models

Academic Qualifications

• BS, MS, or PhD degree (or equivalent experience) in Computer Science, Machine Learning, or related fields

Professional Experience – Minimum

• 2 years of experience working in one of the following or related areas: LLM training/fine‑tuning, evaluations, reinforcement learning, LLM inference, distributed machine learning systems
• Python and PyTorch development experience
• Experience in using LLM agents for your personal or professional use
• Experience in designing and implementing algorithms from scratch (for algorithms focus)
• Experience in dataset curation and generation (for data focus)
• Experience in building or contributing to training/serving infrastructure (for systems focus)
• Experience in designing and deep diving into evaluations (for evals focus)

Preferred Skills

• Expertise in one or more of PyTorch, Ray, Triton, CUDA C++
• Strong knowledge of literature on RL, LLM reasoning, and tool use
• Experience in training or using LLM agents for SWE tasks
• Deep understanding of reinforcement learning principles
• Experience implementing distributed learning algorithms
• Contributions to published research and/or open‑source ML software

$150,000 - $450,000 a year

Compensation

$150,000 – $450,000/year + discretionary performance bonus + benefits

The posted salary range represents the company’s good faith estimate of the base compensation for this position upon hire. The actual base compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, and specific business needs. In addition to base salary, total compensation includes an annual discretionary performance bonus and comprehensive benefits.

Benefits Include

• Comprehensive medical, dental, and vision benefits
• Bonus
• 401K Plan
• Generous paid time off, sick leave and holidays
• Paid Parental Leave
• Employee Assistance Program
• Life insurance and disability

This position is eligible for visa sponsorship.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.