The Opportunity
A live autonomous trading platform running 24/7 agent fleets across dozens of concurrent strategies is hiring a Senior AI Engineer to build the intelligence layer that makes the fleet learn from itself. This is a production role with immediate, measurable feedback — your work either makes the agents more money or it doesn't. Remote, EST timezone.
Your Responsibilities
Design and implement feedback loops connecting trade outcomes back to strategy improvement across signal selection, risk parameters, position sizing, and timing
Build the evaluation framework that distinguishes genuinely predictive signals from noise across shifting market conditions
Develop automated strategy generation and testing, including backtesting against real fleet data and surfacing deployment candidates
Build higher-order agents that autonomously monitor, diagnose, and improve the fleet without human intervention
Develop performance attribution systems that decompose every trade into component drivers and feed insights back into strategy design
Manage fleet coordination across concentration risk, capital allocation, and the exploration vs exploitation balance
Own the model and inference stack from external LLM dependency toward domain-specific, owned intelligence
Build the telemetry and data capture layer that makes continuous learning possible at scale
Your Background
ML engineering in production with trained, deployed, and maintained models that directly impact business outcomes
Reinforcement learning or online learning experience building systems that learn from real-world outcomes rather than static datasets
You have closed the loop end-to-end in production, meaning predictions generate actions, actions generate outcomes, and outcomes improve the model, with measurable results
Strong Python engineering as primary language, comfortable with Go or TypeScript for production services
Experience building data pipelines and distributed systems
Financial ML experience including signal generation, alpha research, or portfolio optimisation is a strong plus
LLM fine-tuning and serving experience including PEFT/LoRA or vLLM is a strong plus
Multi-agent systems design and onchain or DeFi protocol experience are strong plusses
The Package
$175,000 to $250,000 base salary depending on location and experience
Approximately 1% initial equity grant valued at $230,000 at last round, projected to double within six months
Total all-in starting comp of approximately $450,000
Team-wide eligibility for salary increases and bonuses tied to revenue and usage
Pro-rata participation in a planned 2026 token launch