AI Research Intern, PhD (Full Time- Summer)

We are looking for a PhD-level AI Research Intern who will work Full Time for an 4-month summer term to join Assent’s AI & Innovation team. This internship is ideal for researchers who enjoy building and experimenting and who want to apply LLM agent research to impactful, production-oriented use cases.

You will explore how LLMs can act as intelligent agents, autonomously reasoning, planning, and collaborating across data systems to solve complex enterprise problems. Your work will directly contribute to the design and prototyping of next-generation AI features that enhance Assent’s sustainability and compliance platform.

Eligible candidates will be asked to submit details regarding their relevant knowledge and experience, in addition to a resume, during the application process. These details are highlighted at the end of the job ad.

 In this role you will gain: 

• Hands-on experience developing LLM-driven prototypes in a real-world enterprise environment.
• Exposure to challenges of AI alignment, observability, and deployment in production ecosystems.
• Mentorship from senior AI and MLOps engineers working on cutting-edge AI and LLMOps frameworks.
• Opportunity to shape AI features that directly impact global supply chain sustainability.

Key Requirements & Responsibilities 

• Research and prototype LLM-based agent architectures, exploring task decomposition, reasoning, and collaboration between agents.
• Implement and evaluate proof-of-concept AI systems using open-source or proprietary LLM models and frameworks..
• Develop scalable experiment pipelines to assess model behavior, safety, and reliability.
• Build and optimize Python-based backend components, including prompt chains, vector stores, and evaluation tooling.
• Integrate prototypes with internal data systems and APIs, simulating realistic enterprise environments.
• Collaborate with ML engineers and product teams to define success metrics and transition promising prototypes toward production.
• Document findings in internal research reports, technical memos, and demonstrate the results.