Machine Learning Engineer

The Opportunity

As a Machine Learning Engineer at 
Menos AI
, you will design, build, and optimize the specialized AI agents that power our research intelligence platform for institutional asset managers. Our platform processes large-scale financial data to deliver actionable insights that transform how investment teams operate.  

You will work across multi-LLM pipelines (Anthropic, OpenAI, Gemini), agentic orchestration frameworks, and production infrastructure to ship AI capabilities that integrate seamlessly into our clients’ workflows. If you thrive on owning end-to-end product development and want to define a new era of human–AI collaboration in finance, this role is for you.  

Responsibilities

• Build AI Agents for Financial Workflows:
   Develop specialized agents for asset management processes—narrative extraction, sell-side research processing, trade idea classification, and analyst credibility scoring.

• Design and Orchestrate LLM Pipelines:
   Architect multi-model orchestration pipelines, engineer prompts, and build robust evaluation frameworks to ensure quality at scale.

• Own End-to-End ML Development:
   Contribute across the full ML lifecycle: data engineering, model selection, fine-tuning, inference optimization, and evaluation pipelines.

• Architect Reliable Production Systems:
   Build secure, scalable infrastructure to serve ML models, including RAG pipelines, hybrid search (MongoDB Atlas), and low-latency APIs.

• Prototype and Innovate:

   Rapidly develop proofs of concept and iterate on emerging AI tools to keep Menos AI at the frontier of applied AI in finance.

Minimum Qualifications

Technical Foundations

• Proven proficiency in algorithms, data structures, and software engineering (
  Python required
  ; additional languages a plus).
• Hands-on experience building applications with 
  LLM orchestration frameworks
   (e.g., LangGraph or similar).
• Working knowledge of foundation models, 
  Retrieval-Augmented Generation (RAG)
  , and agentic AI architectures.

End-to-End ML Experience

• Demonstrated ability to handle data engineering, model training/fine-tuning, and serving pipelines.
• Understanding of 
  MLOps practices
  , distributed training, and CI/CD for ML systems.

NLP and Text-Heavy Workflows

• Hands-on experience with NLP at scale: document processing, text classification, information extraction, or summarization using modern 
  transformer-based models
  .

Professional Experience

• 3+ years of relevant experience in software engineering or machine learning engineering.

**
Preferred Qualifications**

• Large-Scale Infrastructure:
   Experience with distributed computing frameworks, GPU-accelerated workflows, and low-latency model serving.
• Financial Domain:
   Familiarity with financial market data, credit/equity research, or processing unstructured documents (SEC filings, research reports).
• Startup Mindset:
   Experience in fast-moving environments with a track record of owning problems end-to-end.
• Seniority:
   5+ years of experience for senior-level consideration.

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.