Research Internship 2026 (Masters'/PhD)

Deep Insight Labs; Cambridge (MA); On-site; USD 25,000 - 35,000; Full time

Benefits offered by this job

Joint academic–industry supervision

Direct mentorship on research

Access to compute resources

Job summary

Deep Insight Labs is seeking a Research Engineer intern for Financial Reasoning, dedicated to developing innovative AI systems for investment analysis. The role involves working on financial knowledge graphs and LLM-based reasoning.

Ideal candidates are Master’s or PhD students in Computer Science with strong ML foundations. Opportunities include mentorship, academic–industry collaboration, and publishing in top-tier venues.

Qualifications

• Currently pursuing a Master’s degree or PhD in Computer Science, AI, or related field.
• Strong foundations in machine learning and deep learning.
• Experience with Python and at least one ML framework.

Responsibilities

• Work on financial knowledge graph modeling and representation learning.
• Translate research ideas into production-ready models.
• Submit research to top-tier venues like NeurIPS or ICML.

Skills

Machine learning

Deep learning

Python

PyTorch

Natural Language Processing

Knowledge graphs

Graph Neural Networks

Education

Master’s degree in Computer Science

PhD in AI or related field

Job description

Research Engineer for Financial Reasoning (LLMs)

About Deep Insight Labs

Deep Insight Labs is an applied AI research company building agentic AI systems for investment research and financial reasoning. Our flagship platform, Vector, combines large language models, structured knowledge representations, and human‑in‑the‑loop reasoning to solve complex, real‑world analytical problems faced by investors and financial professionals.

We operate at the intersection of cutting‑edge AI research and production‑grade systems, with active efforts to publish in top‑tier ML conferences and journals while deploying novel models into real products.

Internship Overview

We are seeking a highly motivated Master’s student in Computer Science (or related field) for a research and development internship. The intern will work on novel methods at the intersection of knowledge graphs, representation learning, and LLM‑based reasoning, with joint supervision from Deep Insight Labs and Zhongtian Sun, Assistant Professor in AI (MILA, Cambridge, Oxford, University of Kent)

This internship is designed for candidates who are serious about research excellence and want to see their work both published and deployed.

Research Focus

You will work on one or more of the following areas:

• Financial knowledge graph modeling (entities, events, relationships)
• Graph neural networks (GNNs) and representation learning
• Temporal and heterogeneous graphs
• Learning structured representations from unstructured financial text
• Joint embedding of graphs, documents, and numerical signals
• Contrastive and self‑supervised learning approaches
• Financial Reasoning with LLMs
  • Multi‑step reasoning and planning with LLMs
  • Integrating symbolic structures (graphs, rules) with neural models
  • Explainability, attribution, and reasoning traceability
• Translating research ideas into production‑ready models
• Evaluating models under real‑world constraints (latency, robustness)Building experimental pipelines and benchmarks

Expected Outcomes

• Submission to a top‑tier venue (e.g. NeurIPS, ICML, ICLR, KDD, WWW, or leading journals)
• Production deployment of research ideas into Deep Insight Labs’ platform
• Open‑source contributions (where appropriate)

Who Should Apply

We are looking for candidates who:

• Are currently pursuing a Master’s degree/PhD in Computer Science, AI, or related field
• Have strong foundations in machine learning and deep learning
• Are comfortable with Python and at least one ML framework (PyTorch preferred)
• Have prior exposure to NLP, graphs, or representation learning (coursework or projects)
• Are interested in bridging theory and practice
• Can work independently and communicate research ideas clearly

Nice to Have (but not required):

• Experience with knowledge graphs or GNNs
• Familiarity with LLMs and prompting / fine‑tuning techniques
• Prior research experience or publications
• Interest in finance or economic reasoning

What We Offer

• Joint academic–industry supervision
• Direct mentorship on research framing, experimentation, and writing
• Opportunity to co‑author a top‑tier publication
• Experience deploying novel AI models into production
• Access to compute resources and proprietary datasets
• A fast‑moving, research‑driven environment with real‑world impact