Senior AI/ML Quant Research Engineer & Associate Vice President

Goldman Sachs; Singapore; On-site; SGD 100,000 - 150,000; Full time

Job summary

A leading global investment firm is seeking a Quantitative AI/ML Researcher in Singapore. This role involves applying machine learning and quantitative analysis to high-impact financial projects, including developing alpha-generation models and market-making systems. Applicants should possess a Master's degree in a quantitative field, programming proficiency in Python, and a strong foundation in machine learning. Experience in a quantitative role at a top institution is preferred. Competitive salary and professional development opportunities offered.

Benefits

Diversity and inclusion initiatives

Training and development opportunities

Wellness and personal finance offerings

Qualifications

• Expert-level programming proficiency in Python and experience with its scientific computing ecosystem.
• A profound understanding of machine learning techniques and architectures.
• Proven ability to independently conduct research and manage complex datasets.

Responsibilities

• Spearhead the end-to-end lifecycle of AI/ML models and their production deployment.
• Design, train, and validate models for predictive tasks in complex financial time series.
• Integrate state-of-the-art XAI methodologies to ensure model transparency and interpretability.

Skills

Python programming

Machine Learning

Statistical methods

Communication skills

Education

Master’s degree in Computer Science, Statistics, Quantitative Finance, Mathematics, Physics, or Electrical Engineering

Tools

NumPy

Pandas

Scikit-learn

PyTorch

TensorFlow

Job description

Your Impact

As a Quantitative AI/ML Researcher, you will be at the forefront of financial innovation. You will have the unique opportunity to apply your deep expertise in machine learning and quantitative analysis to high-impact projects, from developing sophisticated alpha-generation models to engineering state-of-the-art market-making and pricing systems. This role offers end-to-end ownership, from initial research and prototyping to deploying scalable, robust models into our production trading environment. You will tackle the unique challenges of applying AI in the high-stakes, non-stationary world of quantitative trading and help shape the future of finance.

• Model Architecture & Implementation: Spearhead the end-to-end lifecycle of AI/ML models, from initial research and ideation through to production deployment, with a clear focus on driving measurable commercial impact.
• Advanced Predictive Modeling: Design, train, and validate novel models for predictive tasks in complex financial time series, including deep learning, reinforcement learning, and state-space models.
• Explainable AI (XAI) & Governance: Integrate and advance state-of-the-art XAI methodologies to ensure model transparency, interpretability, and robustness. Satisfy the rigorous demands of internal model validation, risk management, and regulatory frameworks.
• MLOps & Engineering Excellence: Engineer and maintain high-quality, production-grade code and resilient data pipelines for high-volume, low-latency financial data. Adhere to and promote best practices in MLOps for versioning, containerization, continuous integration/deployment, and real-time monitoring.

Core Qualifications

• A . or Master’s degree in a quantitative discipline such as Computer Science, Statistics, Quantitative Finance, Mathematics, Physics, or Electrical Engineering.
• Expert-level programming proficiency in Python and deep experience with its scientific computing and machine learning ecosystem (., NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).
• A profound theoretical and applied understanding of machine learning techniques, including LLMs, deep learning architectures, reinforcement learning, probabilistic models, and classical statistical methods.
• Proven ability to independently conduct research, manage complex datasets, and solve challenging, open-ended problems with a data-driven approach.
• Exceptional communication and interpersonal skills, with the ability to articulate complex technical concepts to both specialist and non-specialist audiences.

Preferred Qualifications

• Min. 3 years (for Associate) / 8 years (for VP) of distinguished professional or academic research experience, demonstrated by a track record of building and fine-tuning large-scale deep learning models (., Transformers) for sequential or time-series data.
• Prior experience in quantitative role at a leading buy-side or sell-side institution (., quantitative trading, statistical arbitrage, high-frequency market making).
• Direct, hands-on experience applying foundation models (., LLMs) and transfer learning techniques to novel, non-NLP domains.

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at /careers.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.