AI Research Intern, PhD (Full Time- Summer)

Job Description

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.

Qualifications

We strongly value your talent, energy and passion. It will also be valuable to Assent if you have the following qualifications.

• Currently pursuing a PhD (3+ years completed) in Computer Science, Machine Learning, AI, or a related discipline, available to work full time during the summer term (4-month)
• Strong coding and prototyping skills in Python, including familiarity with one or more of:
  • PyTorch, TensorFlow, or similar ML frameworks
  • LLM agent frameworks (LangChain, LlamaIndex, DSPy, AutoGen, or Semantic Kernel)
  • Vector databases (FAISS, Chroma, Pinecone, or Milvus)
  • RAG and retrieval systems using embeddings and knowledge graphs
• Deep understanding of LLM internals, including prompting strategies, fine-tuning, and model evaluation.
• Experience with cloud-based development (AWS) and modern MLOps or LLMOps workflows is an asset.
• Strong experimental design, data analysis, and communication skills.

To be submitted with your resume:

1. Coursework & Technical Foundations

Please list any courses you have taken related to LLMs, deep learning, reinforcement learning/planning, information retrieval, or multi-agent systems. Include brief notes on key concepts or tools covered.

2. Applied LLM / Agentic AI Projects

Describe one or two significant projects where you worked with LLMs or agentic AI systems.

• What problem were you solving?

• What models, frameworks (e.g., LangChain, AutoGen), or architectures did you use?

• What was your specific contribution?

3. Retrieval & RAG Systems

Share any experience you have building retrieval or RAG-based systems.
Please include details on embedding models, vector databases, or knowledge graph components you implemented.

4. Experimentation & Evaluation

Describe a research experiment you designed and executed.
Highlight your evaluation methodology, metrics used, and what insights or outcomes you produced—especially any related to LLM behavior, or reliability.

5. Prototyping & Engineering Skills

Briefly summarize your hands-on experience building AI prototypes.
Include experience with backend components, prompt pipelines, APIs, or integrating models with data systems.

Additional Information

Life at Assent

Wellness: We believe that you and your family’s well being is important. As a result, we offer vacation time that increases with tenure, comprehensive benefits packages (details vary by country), life leave days and more.

Financial Benefits: It’s not all about the money – well, it’s a little about the money. We understand that financial health is important and we offer a competitive base salary, a corporate bonus program, retirement savings options and more.

Life at Assent: There is purpose beyond your work. We provide our team members with flexible work options, volunteer days and opportunities to get involved in corporate giving initiatives.

Lifelong Learning: At Assent, curiosity is not only valued but encouraged. You will receive professional development days that are available to you the day you start.

At Assent, we are committed to growing and sustaining an environment where our team members feel included, valued, and heard. Our diversity and equal opportunity practices are guided and championed by our Diversity and Inclusion Working Group and our Employee Resource Groups (ERGs).

Our commitment to diversity, equity and inclusion includes recruiting and retaining team members from diverse backgrounds and experiences, and fostering a culture of belonging where all team members are included, treated with dignity and respect, promoted on their merits, and placed in positions to contribute to business success.

If you require assistance or accommodation throughout any part of the interview and selection process, please contact talent@assent.com and we will be happy to help.

We use AI to support parts of our recruitment process, such as note-taking and initial shortlisting based on job-related qualifications. AI does not make hiring decisions. All candidates will speak with a real person, and final decisions are always made by our recruitment team.