Ofertas de trabajo de Desarrollador

At ArrowFin, we build real-time risk intelligence systems for the futures trading industry that detect risky trader behavior before a critical loss occurs. We develop proprietary, high-performance technology operating directly on live financial market data, backed by an engineering team focused on real-time systems and advanced analytics.

2. Role Purpose

We are looking for a Machine Learning Engineer to own the ML modeling, behavioral scoring, and data validation frameworks within our risk intelligence platform. Working closely with our Tech Lead, this is an applied ML role where deep reasoning about real trading data matters more than inventing novel model architectures.

3. Key Responsibilities

• Behavioral Modeling & Data: Design and build scoring models and trader profiles using real-world data across hundreds of millions of trades.
• Labeling & Evaluation: Construct high-quality labeled datasets and define rigorous evaluation frameworks to prevent data leakage, sampling bias, and overfitting.
• Production Deployment: Take models from research notebooks into production Python services complete with typed contracts, unit tests, and fixtures.
• Live Validation & Communication: Validate model behavior under noisy live-trading conditions and present complex technical findings in plain English to non-technical stakeholders.

4. Required Stack & Qualifications

Hard Requirements

• Language & Soft Skills: Strong English proficiency (written and spoken) for daily standups, technical design docs, and presentations.
• Experience: 4+ years of industry experience building and shipping applied ML/Data products in production (not purely academic).
• Production Python: Strong hands-on Python development skills to build production-grade services, test suites, and data pipelines.
• Data & SQL: Strong SQL mastery for working independently with large, messy, real-world datasets (PostgreSQL / Timescale DB).
• AI Tooling & Methodology: Comfortable working independently from ambiguous problem statements and effective at using AI coding tools with high leverage.

Nice to Have

• Background or genuine curiosity in futures markets, trading, or financial risk.
• Experience with LLMs / RAG architecture (we have adjacent AI product initiatives).
• Experience with time-series or tick-level data modeling.