Senior AI Data Scientist

Posted 7 Days Ago
2 Locations
Remote
130K-200K Annually
Senior level
Software
The Role
Lead the design and evolution of agentic systems for Chaos AI, optimizing LLMs in financial workflows, and mentoring engineers and data scientists.
Summary Generated by Built In

Chaos Labs builds technology that powers safer, more accessible financial markets. Our risk management systems, oracles, and AI models secure over $200 billion in assets across protocols including Aave, Jupiter, and GMX, processing more than $5 trillion in transaction volume. We recently launched Chaos AI, a financial intelligence platform that transforms complex market data into actionable insights and brings institutional-grade intelligence to everyone.

The Role:

We’re looking for a Senior AI Data Scientist to lead the design, evaluation, and evolution of the agentic systems behind Chaos AI.

This role sits at the intersection of LLMs, financial data, and decision systems. You’ll own how 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 to move from experimentation to reliable, scalable AI systems that operate under real financial constraints.

Responsibilities:

  • Design and own single and multi-agent systems that reason, plan, and act over complex financial workflows
  • Define agent behavior, memory, and tool-use strategies with a strong emphasis on correctness and controllability
  • Develop and maintain LLM evaluation frameworks covering accuracy, faithfulness, latency, cost, regressions, and edge cases
  • Design structured prompting, schemas, and tool-calling strategies for production LLM systems
  • Build and operate MCP servers, including schema design, permissions, and safety boundaries
  • Analyze model behavior and failure modes, turning qualitative issues into measurable signals
  • Partner with engineering to productionize research insights: observability, retries, state, and reliability
  • Optimize system performance and cost across models, workflows, and agent architectures
  • Mentor engineers and data scientists, setting best practices for applied LLM and agentic systems
  • 6+ years experience in data science, applied ML, or AI-focused software roles
  • 3+ years building production AI / ML systems, with ownership beyond experimentation
  • Deep hands-on experience with LLMs, agentic patterns, and tool-calling systems
  • Strong Python skills and comfort working close to production systems and APIs
  • Experience with RAG pipelines, embeddings, and vector databases
  • Strong intuition for model behavior, trade-offs, and failure analysis

Preferred Qualifications:

  • Experience applying ML or statistical methods to financial (crypto/DeFi a plus)
  • Strong intuition for model behavior in production and how it shifts with data, users, and constraints
  • Track record of building reusable ML or data abstractions that meaningfully improved team velocity or decision-making

Our Perks:

  • Paid Time Off - 21 vacation days + 7 sick days + 8 observed U.S. company holidays
  • Health Coverage - 100% employer-paid options (medical, dental & vision) for you and your dependents
  • FSA / HSA Options - depending on selected health insurance plan
  • Parental Leave - thoughtful policy to support your family needs
  • Wellness Programs - OneMedical, Teladoc, Talkspace, and EAP
  • Career Growth - opportunities in a rapidly expanding, global technology company with personalized professional development
  • Pre-tax Commuter Benefits
  • Compensation & Equity - competitive package aligned with growth and merit
  • Salary and seniority level commensurate with experience (Range: $130K–$150K)

Top Skills

AI
Embeddings
Llms
Ml
Python
Rag Pipelines
Vector Databases
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The Company
HQ: New York, NY
25 Employees
Year Founded: 2021

What We Do

Decentralized blockchain applications introduce a myriad of technical challenges, security vulnerabilities and attack vectors.

With DeFi (decentralized finance) protocols now securing hundreds of billions in value in production, the stakes have never been higher. With new technological primitives and bustling innovation, new security paradigms are required. dApps leverage open source modules and often consume other protocols in order to create new applications. This introduces a dependency heavy software architecture which makes it an ideal candidate for runtime verification.

Chaos Labs is a cloud platform which enables teams to create high-fidelity agent and scenario-based simulations on mainnet forks, offering a real-world testing environment. By providing a rich library of customizable agents and scenarios, teams can rapidly speed up development and reduce their go-to-market time, helping them stay competitive without compromising on the security of their protocol.

Additionally, Chaos Labs focuses on developer tooling and cloud infrastructure, allowing teams to move fast on stable infrastructure. The platform is currently live for protocols on the Ethereum network and later expanding to additional blockchains such as Terra, NEAR and Polygon.

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