Machine Learning Engineer Intern

About the Role

As a Machine Learning Engineer Intern at 
Menos AI
, you won’t just observe—you will work alongside our engineering team to build and improve the AI agents powering our research intelligence platform for institutional asset managers.  

Our platform processes large-scale financial data to deliver actionable insights for investment teams. This is a hands-on role where you’ll contribute production-level code, gain experience with multi-LLM pipelines, agentic AI frameworks, and financial NLP, and receive mentorship from engineers shipping products to some of the world’s largest asset managers. If you’re eager to learn fast and build at the intersection of AI and finance, this is for you.  

Duration:

 12–16 weeks

What You’ll Work On

• Contribute to AI Agent Development:
   Help build specialized agents for financial workflows, such as research document processing and trade idea extraction.
• Support LLM Pipeline Work:
   Assist with prompt engineering, evaluation framework development, and testing across multi-model pipelines (Anthropic, OpenAI, Gemini).
• Build Evaluation & Data Tooling:
   Develop scripts, dashboards, and utilities for ML evaluation, data processing, and pipeline monitoring.
• Prototype New Capabilities:
   Run experiments with emerging AI tools, build proofs of concept, and present findings to the team.
• Learn Production ML:
   Gain exposure to the full ML lifecycle: data engineering, model serving, RAG pipelines, and infrastructure (MongoDB Atlas, Python, LangGraph).

**
Minimum Qualifications**

• Technical Foundations:
   Strong Python skills and a solid understanding of algorithms, data structures, and software engineering fundamentals.
• AI Knowledge:
   Coursework or project experience in ML, Deep Learning, or NLP; basic understanding of Transformers and LLM applications.
• Education:
   Currently pursuing a Bachelor’s or Master’s in Computer Science, ML, Data Science, or a related field (expected graduation within 12 months or currently in a gap year).
• Tools:
   Exposure to LLM frameworks (LangChain, LangGraph, or LlamaIndex) is a major plus.

Preferred Qualifications

• Prior experience building ML/AI applications (personal projects and open-source count!).
• Experience with NLP tasks on real-world, "messy" data.
• Familiarity with Git, CI/CD workflows, and collaborative development.
• Interest in financial markets, asset management, or fintech.
• A self-starter mentality—comfortable with ambiguity and eager to learn independently.

What You’ll Gain

• Real Impact:
   Direct experience shipping products used by institutional investors.
• Mentorship:
   Work with engineers at the frontier of applied AI.
• Full-Stack Exposure:
   Learn LLM orchestration, RAG, and production infrastructure.
• Startup Growth:
   High visibility in an early-stage company where your work matters.

Why Menos AI?

We aren't just building models; we are building the central intelligence layer for investment organizations. This role allows you to move beyond traditional quant silos and combine quantitative rigor with AI into a unified workflow. You will work alongside top-tier PhDs and technologists to shape the future of factor research.

Compensation:
 We offer competitive salary and equity packages designed to attract and retain the best talent in the industry.