Research & Model Intelligence Lead

Ant-Tech

About The Position

As Research & Model Intelligence Lead, you'll take full ownership of the systems and science that power our edge — from model research and fine-tuning to inference optimization, evaluation frameworks, and the AI agent intelligence layer. You will be expected to lead a team that builds, evaluates, and deploys models that support our investment activities. This is a senior role with real leadership weight. You'll lead a team of ML engineers, NLP specialists, and quantitative researchers — setting research direction, running evaluation cycles end-to-end, and ensuring that model improvements translate to trading performance. You'll partner tightly with traders, strategists, and platform engineers. We're looking for an AI-native, agentic engineer-researcher: someone who instinctively uses LLMs and modern tooling to accelerate experimentation, evaluation, and iteration — and teaches their team to do the same. You create leverage through models, people, and rigorous evaluation.

Requirements

Strong people leader with experience running technical teams through real delivery
Systems thinker who understands the full lifecycle from research to production inference
Comfortable operating in ambiguity and bringing structure through experimentation
Strong project management instincts — able to sequence research bets and manage evaluation cycles
AI-native and scrappy — focused on leverage, automation, and modern tooling
Values rigor, measurable outcomes, and impact over complexity or consensus
Experience leading ML, NLP, or research teams shipping models in high-stakes or latency-sensitive environments
Ownership of evaluation and continuous monitoring systems for deployed models
Experience with LLM fine-tuning, prompt optimization, inference serving (quantization, multi-provider racing, GPU orchestration), or agent architectures
Strong applied ML or quantitative research background with a focus on production deployment
Curiosity, learning speed, and ownership mindset (financial markets experience not required)

Nice To Haves

Experience managing senior cross-functional stakeholders and driving alignment
Background in trading, finance, crypto, or similar domains with direct P&L impact
Familiarity with NLP for news or event-driven signal extraction
Ideally based within ±3 hours of EST

Responsibilities

Own the research and model intelligence domain
Take end-to-end ownership of the systems that generate, evaluate, and serve our trading intelligence — including fine-tuned LLMs, prompt engineering pipelines, NLP signal extraction, agent architectures, and evaluation infrastructure.
Lead and scale a team
Act as a true people leader: set research direction, coach performance, run planning, and create clarity across a team spanning ML engineering, NLP, quantitative research, and agent development.
Bridge research and production
Turn model improvements into deployed trading performance. Own the full pipeline from hypothesis through evaluation to production serving — keeping it fast, reliable, and measurable.
Partner with senior stakeholders
Work directly with trading strategists, execution engineers, and platform leads. Translate trading needs into research priorities and keep everyone aligned as strategies evolve.
Build with an AI-first mindset
Use LLMs and agentic workflows to accelerate research processes — including experiment design, evaluation automation, literature synthesis, and knowledge management.
Architect for inference quality and speed
Design model serving, evaluation, and agent orchestration systems that are observable, reproducible, and optimized for performance. Own tradeoffs between model capability and serving performance.
Set the standard
Define how the team designs experiments, evaluates results, reviews model performance, and ships to production — both scientifically and operationally.