Senior DeFi Researcher at ChainML
Remote, Oregon, USA -
Full Time


Start Date

Immediate

Expiry Date

05 Dec, 25

Salary

0.0

Posted On

05 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, Hedging, Documentation, Engineers, Data Analysis, Ethics, Sql

Industry

Financial Services

Description

ABOUT CHAINML

ChainML, the labs company behind Theoriq, is at the forefront of AI-driven decentralized finance by integrating AI with blockchain.
Theoriq is shaping the future of AI-powered DeFi through advanced agent swarm and coordination technology—unlocking the full potential of autonomous agentic finance and introducing a new liquidity layer to Web3. We champion decentralization to ensure an equitable distribution of AI’s benefits while mitigating risks tied to centralized technology control.
We are a remote-first team and hire globally. For this role, we have a strong preference for candidates based in the United States or Canada. Exceptional candidates elsewhere are encouraged to apply.

QUALIFICATIONS

  • Proven, verifiable DeFi P&L (e.g., CLMM LP with hedging, basis/funding, structured yield) with transparent attribution.
  • Deep understanding of on-chain microstructure: AMMs (Uniswap v3/CLMM math), routing/MEV, oracles, gas/latency, L2 nuances.
  • Strong empirical research skills: clean experiment design, skeptical inference, robustness checks, and ablations.
  • Hands-on with Python + SQL for implementing strategies, backtests and data analysis; able to work with EVM logs/events and data from sources like The Graph, Dune, BigQuery or self-hosted archives.
  • Practical risk mindset: position sizing, drawdown/tail-risk control, borrow/funding management, execution slippage/impact awareness.
  • Ability to write concise, execution-ready specs and collaborate tightly with engineers who will implement and operate.
  • Read-level Solidity literacy (to assess contracts, oracles, upgrade patterns); no heavy smart-contract dev required.
  • Bonus: experience with agent/RL evaluation loops; MEV-aware execution; LST/LRT, Pendle curves, cross-margining, vault frameworks.
  • Thrives in a fast-moving startup, embraces ambiguity, and upholds high standards for reproducibility, documentation, and ethics.

How To Apply:

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Responsibilities

ABOUT THE ROLE

Theoriq is seeking a Senior Quant – DeFi to design, test, and deploy production-grade DeFi strategies. In this role, you’ll be a leader in the research team and deeply hands-on: building models, running simulations, and translating high-conviction ideas into live strategies in collaboration with engineering. The ideal candidate has a track record of discovering alpha, has taken multiple strategies from research to mainnet with measurable P&L, is comfortable working directly with on-chain data, and maintains an active, respected presence across Web3 communities.

WHAT YOU’LL DO

  • Alpha discovery


    • Maintain a hypothesis pipeline across LP/CLMM, perps/options, basis/funding, lending/borrowing, yield curves (LST/LRT, Pendle-style), and cross-venue/cross-chain flows.

    • Empirical validation


      • Build and run robust backtests and event-driven sims (tx/log level when needed).

      • Define objective functions (PnL in ETH/USD, Sharpe/Sortino, max DD), capacity, and sensitivity analyses.
      • Specification & implementation


        • Write execution-ready strategy specs: signals, state, parameter bounds, entry/exit, rebalancing/hedging cadence, fail-safes, kill/scale rules.

        • Prototype and implement production code
        • Partner closely with other researchers and engineers through paper shadow prod, staying hands-on in validation and tuning.
        • Risk & controls


          • Set inventory/leverage limits, liquidity/impact budgets, borrow/funding constraints; encode oracle/MEV/latency checks and circuit breakers.

          • Monitoring & attribution


            • Define real-time and post-trade dashboards (fees vs. inventory vs. hedge P&L, slippage, borrow/funding, anomaly alerts).

            • Establish crisp go/hold/kill thresholds.
            • AI-agent integration


              • Express strategies as agent policies/reward functions; contribute datasets, offline evals, and capital-at-risk ramp plans.

              • Market intelligence


                • Track L2/rollup microstructure, intent layers, new primitives, venue/liquidity migrations.

                • Cultivate protocol/MM/data-provider relationships for early access.
                • Documentation & comms


                  • Produce clear research memos, runbooks, and postmortems; present results to product, risk, and leadership.

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