Applied AI Engineer, Quants

OpenAI
London
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Communication","Technical judgment","End-to-end ownership","Problem-solving","Collaboration"]

Partner with quantitative investment and trading firms to apply OpenAI models and Codex to their R&D workflows. Build and debug AI systems, prototypes, evaluation harnesses, integrations, and production accelerators. Make technical decisions across model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Drive complex issues to resolution while leading hands-on workshops and translating enterprise deployment needs into product requirements.

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FursaFursa
OpenAI
OpenAI
14 hours ago

Applied AI Engineer, Quants

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 13 hours agoStatus: Live

Job Summary

Partner with quantitative investment and trading firms to apply OpenAI models and Codex to their R&D workflows. Build and debug AI systems, prototypes, evaluation harnesses, integrations, and production accelerators. Make technical decisions across model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Drive complex issues to resolution while leading hands-on workshops and translating enterprise deployment needs into product requirements.
Location: London
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Work directly with quantitative investment and trading firms to identify opportunities across research, data analysis, and software development, translating needs into implementations and measurable outcomes.
  • •Design, build, and deploy AI systems that solve customer problems and produce measurable business outcomes.
  • •Hands-on code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators.
  • •Make sound technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, governance, and operational readiness.
  • •Diagnose complex implementation challenges, reproduce failures, test hypotheses, and lead technical workshops; translate deployment feedback into product requirements.

Pay and Benefits

Perks:Relocation

Key Requirements

  • •Have hands-on experience with LLMs, including deploying LLM systems (Codex experience is a plus).
  • •Be highly proficient in Python and able to build and debug research tools, data workflows, or software systems.
  • •Bring a rigorous approach to evaluating quantitative, statistical, or machine-learning systems and assessing AI outputs and workflows.
  • •Have experience with enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost.
  • •Demonstrate substantial personal contributions in code, architecture, evaluation, debugging, or production engineering, and communicate clearly with technical leaders and executives.
Skills:CommunicationTechnical judgmentEnd-to-end ownershipProblem-solvingCollaboration
Tech Stack:PythonLLMsCodex

Company Brief

OpenAI
Develops and deploys advanced generative AI models (including ChatGPT and DALL·E) and AI infrastructure, providing APIs and consumer products to accelerate safe AGI for broad benefit.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Hectocorn (USD 100B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2015
Glassdoor
Glassdoor: 4.4
WebsiteLinkedInGlassdoor