We're looking for our first Machine Learning Engineer to join a large Private Equity firm. We're looking for someone who's capable of leading in the face of ambiguity. You'll shape product direction, build foundational infrastructure, and work shoulder-to-shoulder with senior executives.
What You'll Be Doing:
You'll be driving end-to-end ML initiatives across internal tools and client-facing POCs. Projects include:
- Building AI-powered tools for internal teams (deals, investor relations, legal)
- Prototyping LLM applications for automating tasks like NDA analysis, investor Q&A, and document search
- Handling everything from cloud infrastructure setup and GPU access to model development and simple front-end integrations
- Designing and implementing RAG pipelines, performing model fine-tuning, and building search/information extraction systems
What We're Looking For:
Must-Haves:
- 3-5 years of experience in ML engineering, ideally with production experience
- Strong Python and ML ecosystem skills (PyTorch, Hugging Face, LangChain, etc.)
- Experience working with LLMs or NLP-heavy projects (e.g., RAG, entity extraction, summarization)
- Ability to work independently in an ambiguous, fast-moving startup environment
- Comfortable with full-stack-ish tasks (e.g., integrating models into simple UIs)
Nice-to-Haves:
- Master's degree in CS, ML, or a related field
- Experience with computer vision or multi-modal LLMs
- Familiarity with finance workflows or legal tech
- Experience deploying models to production in cloud or GPU-accelerated environments
Why This Role?
- True greenfield opportunity - you're the first engineer
- High visibility and executive exposure
- Culture that values pragmatism, velocity, and impact
- Opportunity to shape technical vision, not just execute on it
Logistics:
- Location: Onsite in NYC (4 days/week)