MarketCatalyst Analytics LLC · Careers
AI/ML Engineer
AI/ML Engineer — LLM Pipelines and Research AI
Own the LLM pipelines, attribution models, RAG grounding and evals behind every AI read in the product.
This is a remote role open to candidates who live in Texas. You can work from anywhere in the state.
About the company
MarketCatalyst (https://marketcatalyst.ai) is an AI-powered stock market research terminal for traders and investors: 16 workspaces covering movers, earnings, analyst actions, macro, SEC EDGAR insider and 13F ownership, ETFs, IPOs, screeners and AI recaps, plus a per-ticker Stock Intelligence view. Its content is generated by automated AI pipelines over sourced market data. It is a research and information platform that does not offer trade signals or investment advice. We're early-stage and founder-led, with a free tier and Pro ($29) and Elite ($79) plans.
What you'll do
- Build and run the LLM pipelines that generate the daily and weekly recaps, "What Matters Now" briefs and per-ticker reads from our normalized market data.
- Improve Why It Moved attribution (linking price moves to news, filings, earnings and analyst actions) and the Why It Could Move catalyst scoring models.
- Build retrieval and grounding (RAG) for the AI research chat, Thesis Lab and Thesis Monitor so answers cite the underlying data and filings and decline when the evidence isn't there.
- Create evaluation sets and automated checks for factual accuracy, number consistency, hallucinated causes and advice-like language. Run them on every prompt or model change.
- Manage cost, latency and reliability: model choice, caching, batching, fallbacks and monitoring for scheduled and interactive workloads.
- Integrate AI features into the production Next.js app and APIs alongside the rest of the engineering work.
What you bring
- 6+ years in software or ML engineering, including at least one LLM-powered feature shipped to production.
- Strong Python. Comfortable reading and writing TypeScript in a Next.js codebase.
- Hands-on experience with RAG: chunking, embeddings, vector or hybrid search, reranking and citation of sources.
- Experience designing LLM evaluations (golden sets, LLM-as-judge with spot checks, regression tests), not just eyeballing outputs.
- Solid fundamentals in classical ML and statistics for attribution and scoring work (feature engineering, validation, avoiding leakage and look-ahead bias with time-series data).
- Production habits: logging, monitoring, cost tracking and safe rollouts.
Nice to have
- Experience with financial or market data, news-event attribution or event studies.
- Experience with structured outputs, function calling or agent frameworks, and their failure modes.
- Experience with Postgres, including pgvector or another vector store.
- Interest in markets and in building AI that explains rather than predicts.
What we offer
- Compensation: $80,000–$120,000 per year
- Equity may be offered to the right candidate.
- Paid time off and flexible hours.
- Ownership of the AI system at the center of the product, early enough to set its architecture and standards.
How to apply
Send your resume to hr@marketcatalyst.ai with the subject line "Application: AI/ML Engineer". Include a short note (or link) on an LLM system you shipped: how you measured whether it was right and what you changed as a result.
Equal opportunity
MarketCatalyst Analytics LLC is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information or any other status protected by applicable law. If you need an accommodation during the application process, email hr@marketcatalyst.ai.