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.