AI/ML Engineer
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Role details
Tech stack
Job description
- Youâll build and own core AI/ML systems - designing and improving agentic AI workflows for automated document retrieval from dozens of private portals, our proprietary extraction and normalization engine that processes complex PDFs/Excels/reports, intelligent validation with full audit trails, and pipelines that turn unstructured private market data into accurate, structured, real-time insights using various techniques, including feedback loops or data gathering agents.
- Youâll brainstorm - Weâre not looking for someone to just take tickets-we want you in the room helping shape AI strategy, model choices, evaluation frameworks, and product direction.
- Youâll work with clients - From pitching customers, to designing features, to soliciting feedback, youâll do some non-engineering work. We believe in all-rounded team members.
- Youâll champion best practices and guide others - As a B2B SaaS platform, our technology needs to be secure, robust and scalable. Youâll help set and maintain standards and mentor future team members.
Requirements
- Youâre proactive and hands-on - someone who takes initiative, figures things out, and keeps things moving.
- You learn and adapt quickly - someone who approaches problems with creativity and energy, and is resourceful, adaptable and excited by tough challenges.
- Youâre customer-oriented - whether building AI web scraping agents, data extraction pipelines, or AI chat features, you keep customers front of mind and focus on delivering accurate, auditable insights that save thousands of hours while creating delightful and efficient experiences.
- Youâre collaborative - someone who values transparency, good communication, and knows that the best outcomes come from working well with others.
- Youâre experienced and thoughtful - youâre a strong AI/ML engineer with 5+ years building production-grade AI systems, particularly around LLMs, agents, evals, or data extraction/normalization pipelines. Strong Python skills are required. Experience shipping reliable ML features to real users (especially in data-heavy or fintech environments) is highly valued. Bonus points if youâve contributed to open source.
Benefits & conditions
- Youâll have real impact - We are at an inflection point - your work will directly shape our product, team, and company trajectory.
- Youâll be supported - Weâre committed to helping you do your best work and grow both professionally and personally.
- Youâll be rewarded - Competitive salary, meaningful equity, and benefits including unlimited vacation, healthcare, and retirement plans.
- Youâll grow fast - We move quickly, think deeply, and believe in learning through doing. Youâll be surrounded by smart, driven, kind people.
About the company
Tetrix is a fast-growing startup on a mission to empower institutional investors to confidently invest in alternative markets (think Bloomberg, but for private markets). Our AI-native product transforms messy, unstructured private market data into real-time insights, combining automated document retrieval, AI-powered data extraction, and on-demand portfolio analytics - all in one seamless platform. We are growing quickly to becoming a category-defining product, and are working with some of the worldâs leading capital allocators. This is a unique opportunity to join a talented and driven team that wants to build next-generation infrastructure in financial markets, and is backed by stellar investors that include Innovation Endeavors, Eric Schmidtâs VC firm, and angels from BlackRock, CPPIB, SoftBank, Lending Club, and Plaid.
ď¸ Who we are
We are a small but mighty startup with deep industry background and expertise in both financial markets and modern technologies. Weâve worked hard to build a culture of trust, high ownership, and curiosity-where everyone feels empowered to contribute, challenge ideas, and grow together. We are led by our two co-founders, Olivier (CEO) & Naunidh (CTO), who met on the first day of school whilst pursuing their MBAs at Stanford and co-founded Tetrix in the Summer of 23.
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