Applied Research, Quantitative Finance

Prime Intellect

. Build environments, evaluations, agents, and post-training methods for quantitative research and systematic decision-making .

Posted 10/19/2026full-timeRemote • California • United StatesMid-LevelSenior💰 $150,000 - $300,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building environments and agents for quantitative research, with strong capabilities in reinforcement learning, experimental design, and model evaluation. Proficient in Python and skilled in developing robust systems that facilitate systematic decision-making and hypothesis testing.

Highest-signal resume keywords

Reinforcement LearningQuantitative ResearchPython ProgrammingExperimental DesignSystematic Trading

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model TrainingPost-Training SystemsAgent DevelopmentTime-Series ModelingEconometricsFinancial SimulationEvaluation DesignBacktestingData AnalysisSimulation Tools

Soft Skills

Strong Experimental JudgmentProblem OwnershipCollaborationAdaptabilityCommunication

Tools & Technologies

Analytical ToolsExecution ToolsMonitoring SystemsOpen-Source SystemsResearch Artifacts

Industry Keywords

Market MicrostructureHypothesis FormationLook-Ahead BiasData LeakageOverfittingRisk ConstraintsOperational ConstraintsFailure AttributionAdverse ConditionsPoint-In-Time Data

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Build environments, evaluations, agents, and post-training methods for quantitative research and systematic decision-making
Turn workflows into tasks, environments, evaluations, and reward signals
Run post-training experiments against real baselines and determine whether gains come from the model, data, harness, inference, or infrastructure
Build quantitative-research environments for hypothesis formation, analysis, backtesting on point-in-time data, result diagnosis, and iterative testing
Design rewards and evaluations distinguishing durable improvement from look-ahead bias, data leakage, overfitting, favorable execution assumptions, hidden concentration, and tail risk
Train long-horizon agents to use data, research, coding, simulation, and portfolio tools while preserving provenance and respecting risk constraints
Build environments with realistic market mechanics, transaction costs, latency, capacity, and operational constraints
Develop agents that conduct quantitative research, use analytical and execution tools, inspect evidence, and recover from failed hypotheses
Create verifiers and evaluations for robust out-of-sample behavior across assets, horizons, regimes, and adverse conditions
Build production loops with monitoring, human authority, regression gates, and failure attribution across models, data, simulation, and infrastructure
Work directly with customers, users, or research partners while maintaining a substantive research agenda
Turn reusable work into shared research, open-source systems, and product capabilities

Requirements

What you’ll need

Depth in RL, agents, or post-training systems and ability to become fluent in quantitative research
Prior work in systematic trading, market microstructure, time-series modeling, econometrics, or financial simulation is useful but not required
Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops
Strong experimental judgment: meaningful baselines, careful trace inspection, clear failure attribution, and willingness to change direction when evidence changes
Strong Python
Ability to build artifacts that other researchers and engineers can run, inspect, and extend
Comfort owning ambiguous problems and keeping partners and teammates current
Publications, open-source systems, benchmarks, or shipped products as evidence of exceptional work

Benefits

Comp & perks

Equity incentives
Flexible Work (San Francisco, New York, London, or remote)
Visa Sponsorship & relocation support
Professional Development budget
Team Off-sites & conference attendance