Applied Research – Artificial Intelligence – London – Associate

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Website Talent Ali

Applied Research – Artificial Intelligence – Associate

Goldman Sachs • London, United Kingdom Division: Engineering (Global Strategist Groups) Employment Type: Full-time

Role Overview

At Goldman Sachs, AI Researchers are at the intersection of quantitative finance and cutting-edge computer science. As an Associate in Applied AI Research, you will not just be conducting theoretical research; you will be “turning data into action” by building massively scalable machine learning systems that power global markets. You will bridge the gap between academic innovation and production-ready financial engineering, solving complex problems in low-latency infrastructure and high-stakes decision-making.

Key Responsibilities

  • Collaborative Development: Work across global strategist groups to advance production-level ML systems and applications.

  • Full-Cycle Research: Conceptualize, experiment with, and rigorously assess AI/ML-based software systems for financial use cases.

  • Engineering Excellence: Develop and maintain high-quality, production-ready code. You are expected to build the libraries and frameworks that ensure systems are reliable and testable.

  • Technical Leadership: Take ownership of cross-team projects, demonstrating the ability to lead complex technical initiatives.

  • External Engagement: Represent the firm within open-source communities and at global AI/ML conferences.

Required Qualifications

  • Education: Master’s or Ph.D. in Computer Science, ML, Mathematics, Physics, Statistics, or Quantitative Finance (or equivalent industry experience).

  • Professional Experience: 1–3 years of industry experience in AI/ML.

  • Programming Mastery: Strong hands-on experience in building and maintaining large-scale Python applications.

  • Domain Expertise: Extensive experience in software development specifically for quantitative investment workflows (Equities, Fixed Income, or Multi-Asset strategies).

Primary AI/ML Domains

You will contribute to a broad spectrum of research areas, including:

  • Natural Language Processing (NLP): For sentiment analysis and document ingestion.

  • Time Series Analysis: For market prediction and risk modeling.

  • Information Retrieval & Recommender Systems: For client insights and internal data discovery.

  • Deep Learning: For complex pattern recognition in non-linear financial data.

Diversity and Representation at Goldman Sachs

Goldman Sachs publicly tracks its progress in fostering an inclusive workforce. According to the firm’s most recent People Strategy reports:

  • Global Workforce: The firm employs approximately 45,000+ people globally.

  • UK Diversity Benchmarks: In the UK, the firm has set aspirational goals for its analyst and associate entries, aiming for 9% Black, 14% Asian, and 50% Women representation.

  • Equal Opportunity: The firm maintains a “zero-tolerance” policy toward discrimination based on race, religion, sex, disability, or veteran status.

Interview Preparation Insights

  • The “Quant” vs. “ML” Balance: Goldman Sachs is unique because its AI researchers must understand the math behind the finance. Be prepared to discuss how ML models (like Transformers or LSTMs) handle the “non-stationary” nature of financial time series data compared to static datasets.

  • Coding Rigor: Expect a deep dive into Python internals. They aren’t just looking for someone who can call model.fit(); they want someone who understands memory management, decorators, and building scalable APIs.

  • System Design: Be ready to whiteboard a system that handles high-throughput data with low latency. How do you ensure your ML model doesn’t become a bottleneck in a live trading environment?

  • Financial Logic: Review the basics of the “Greeks” or Fixed Income pricing. You don’t need to be a trader, but you must be able to speak the language of the “Global Strategists” you will be supporting.

    Gemini said

    This summary details the Applied AI Researcher (Associate) position within the Engineering division at Goldman Sachs, London.

    Core Role Summary: Applied AI Researcher (Associate)

    Category Details & Specifications
    Institution Goldman Sachs, Inc.
    Division Engineering (Technology & Global Strategist Groups)
    Location London (Greater London), United Kingdom
    Contract Type Full-time
    Job Grade Associate
    Core Mission Driving firm-wide adoption of cutting-edge AI/ML to transform financial engineering.

    Key Technical Responsibilities

    As an Applied AI Researcher, you will operate at the intersection of quantitative research and production-grade software engineering.

    • Model Innovation: Conceptualizing and experimenting with AI/ML domains including Deep Learning, NLP, Information Retrieval, Time Series Analysis, and Recommender Systems.

    • Production Engineering: Developing, testing, and maintaining high-quality, production-ready code. This includes building libraries and frameworks that ensure systems are reliable and testable.

    • Technical Leadership: Taking charge of cross-team projects and advancing production ML systems that solve complex financial engineering problems.

    • External Representation: Representing the firm at global AI/ML conferences and participating actively in open-source communities.

    Candidate Profile & Qualifications

    Goldman Sachs seeks a hybrid professional who pairs high-level academic research with robust software development skills.

    • Academic Background: Master’s or Ph.D. in Computer Science, ML, Mathematics, Statistics, Physics, or Quantitative Finance.

    • Industry Experience: A minimum of 1–3 years of professional AI/ML experience.

    • Technical Stack: Extensive hands-on experience building and maintaining large-scale Python applications.

    • Domain Expertise: Proven experience in software development for quantitative investment workflows (Equities, Fixed Income, or Multi-asset strategies).

    Diversity & Inclusion Statistics (Firmwide)

    Goldman Sachs provides transparency regarding its workforce composition as part of its commitment to an inclusive environment.

    US Workforce Data (Recent Reporting): | Demographic Group | Representation (All Levels) | | :— | :— | | White | 45.4% | | Asian | 30.5% | | Hispanic/Latino | 10.3% | | Black/African American | 7.7% | | Other/Two or More | 6.1% |

    Gender Representation:

    • Global Workforce: 40% Female / 60% Male.

    • 2023 Campus Analyst Hires: 46% Female.

    Benefits & Company Culture

    • Growth: Extensive training, development opportunities, and firmwide professional networks.

    • Wellness: Comprehensive benefits including personal finance offerings, mindfulness programs, and healthcare.

    • Inclusion: A culture that values “who you are” as a driver of professional excellence, backed by a strong commitment to reasonable accommodations for disabilities.

To apply for this job please visit www.goldmansachs.com.