Senior AI Data Scientist job opportunity at MLabs.

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Date2026-02-13T16:49:33.480Z bot
MLabs Senior AI Data Scientist
Experience: 6-years
Pattern: full-time
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Italy

Senior AI Data Scientist Location: Remote - USA, Europe, Israel Compensation: $130K - $150K We are a leading financial technology firm building the infrastructure for safer, more accessible global markets. Our risk management systems, oracles, and AI models secure hundreds of billions in assets and process trillions in transaction volume across major protocols. We recently launched a cutting-edge financial intelligence platform that transforms complex market data into actionable insights, bringing institutional-grade intelligence to a global audience. We are seeking a Senior AI Data Scientist to lead the design, evaluation, and evolution of the agentic systems behind our financial intelligence platform. This role sits at the intersection of LLMs, financial data, and decision systems. You will own the logic behind how our models reason over data, how agents coordinate and make decisions, and how we rigorously measure quality, correctness, and risk in production AI workflows. You’ll work closely with product, engineering, and research teams to move from experimentation to reliable, scalable AI systems that operate under real-world financial constraints. Key Responsibilities: System Design: Design and own single and multi-agent systems that reason, plan, and act over complex financial workflows. Agent Logic: Define agent behavior, memory, and tool-use strategies with a strong emphasis on correctness and controllability. Evaluation Frameworks: Develop and maintain LLM evaluation frameworks covering accuracy, faithfulness, latency, cost, regressions, and edge cases. Production Implementation: Design structured prompting, schemas, and tool-calling strategies; build and operate MCP servers including schema design and safety boundaries. Optimization: Analyze model behavior and failure modes to turn qualitative issues into measurable signals; optimize performance and cost across workflows. Mentorship: Mentor engineers and data scientists, setting best practices for applied LLM and agentic systems. Experience: 6+ years in data science, applied ML, or AI-focused software roles, with at least 3+ years building production AI/ML systems (beyond the experimentation phase). Technical Depth: Deep hands-on experience with LLMs, agentic patterns, and tool-calling systems. Programming: Strong Python skills and comfort working closely with production systems and APIs. Architecture: Proven experience with RAG pipelines, embeddings, and vector databases. Analytical Mindset: Strong intuition for model behavior, trade-offs, and failure analysis. Preferred Qualifications: Experience applying ML or statistical methods to financial data (crypto/DeFi is a major plus). A track record of building reusable ML or data abstractions that improve team velocity. A strong intuition for how model behavior shifts in production based on data, users, and constraints.

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