Job Summary

We are seeking a Sr. Research Engineer – Machine Learning to join a research-focused organization working at the forefront of Machine Learning, Large Language Models (LLMs), and Multi-Agent AI systems. This is primarily a research position, not a traditional product-development role.

The ideal candidate will be a recent PhD graduate or early-career researcher with a strong foundation in mathematics, statistics, computer science, industrial engineering, or operations research, and a demonstrated interest in conducting original research in AI/ML.

The candidate will work closely with research teams to investigate emerging ML/LLM phenomena, formulate research questions, develop experimental prototypes and proof-of-concepts, analyze results, and contribute to research papers, inventions, and patents.

Key Responsibilities

• Conduct original research in Machine Learning and Artificial Intelligence, with a strong focus on emerging LLM and generative AI technologies.
• Investigate LLMs as research phenomena, including model behavior, architectures, learning capabilities, memory, reasoning, and interaction patterns.
• Research and develop multi-agent LLM systems, including interactions among multiple AI agents and group-level behaviors.
• Explore LLMs as language learners and investigate how language models acquire, represent, and use language.
• Design and implement proof-of-concept systems and experimental prototypes to validate new research ideas.
• Develop research experiments, analyze results, and use quantitative methods to draw meaningful conclusions.
• Apply strong mathematical, statistical, and analytical techniques to ML/AI research problems.
• Investigate applications of LLMs including AI-assisted code generation and other emerging applications.
• Contribute to research publications, technical papers, conference submissions, and internal research documentation.
• Identify opportunities for new inventions, intellectual property, and patentable ideas arising from research.
• Collaborate with researchers and technical teams to formulate hypotheses, conduct experiments, and communicate findings.
• Read and analyze current academic literature and translate relevant research concepts into experimental implementations.
• Build, test, and iterate on experimental ML/AI systems using appropriate programming and ML frameworks.
• Present research findings and technical insights to internal research teams and stakeholders.
• Work through ambiguous and open-ended research problems where the solution may require experimentation and exploration.

Required Qualifications

• PhD or recently completed PhD in one of the following areas:
  • Computer Science
  • Statistics
  • Mathematics
  • Industrial Engineering
  • Operations Research
  • Machine Learning / Artificial Intelligence
  • Related quantitative discipline
• Strong foundation in statistics, probability, mathematics, optimization, or quantitative modeling.
• Research experience in Machine Learning, Artificial Intelligence, LLMs, or related areas.
• Strong programming and prototyping skills, preferably with Python.
• Experience designing and conducting research experiments and proof-of-concepts.
• Ability to independently investigate complex technical problems and formulate research hypotheses.
• Strong analytical and problem-solving skills.
• Ability to read, understand, and contribute to academic research papers.
• Strong written and verbal communication skills.

Ideal Candidate Profile

The ideal candidate is a recent PhD graduate or early-career researcher who is excited about solving open-ended research problems and exploring emerging AI technologies.

Candidates with a PhD in Mathematics or Statistics are encouraged to apply if they have strong ML/AI research experience or the ability to apply their quantitative background to Machine Learning problems. A Computer Science PhD is not mandatory.

The role is particularly suited for someone who wants to learn, experiment, publish research, develop proof-of-concepts, and potentially create new inventions or patents, rather than someone primarily focused on production software development.