At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.
Engineering, which is comprised of our Technology Division and global strategists groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.
Who We Look for
Goldman Sachs is in search of an Applied Artificial Intelligence (Applied AI) Engineer to join our Applied AI Team. As an Applied AI Engineer, your expertise in computer science, statistics, artificial intelligence, and machine learning will be crucial for developing and implementing AI-driven quantitative technologies that will contribute to revenue growth and foster innovation within the firm.
In this role, you will have the chance to work with various teams across different divisions on groundbreaking projects that integrate artificial intelligence with quantitative finance. As an Applied AI Strategist, you will address the specific challenges that arise in applying machine learning systems to the financial sector. Join us in pushing the limits of what is achievable at the convergence of quantitative finance and artificial intelligence!
Responsibilities:
- Create and implement scalable AI models to achieve business objectives.
- Perform experiments to enhance the efficiency of models.
- Articulate ideas and findings clearly in both spoken and written forms across different departments.
- Work collaboratively with team members to push forward the development of machine learning systems and applications.
- Write, test, and uphold high-quality code ready for production.
- Show technical leadership by leading projects that span multiple teams.
Required Qualifications
- A Master's or Ph.D. degree in Quantitative Finance, Math, Physics, Finance Engineering, or equivalent relevant industry experience.
- Programming experience in Python and strong knowledge of data structures, algorithms, and software engineering practices.
- Excellent understanding of machine learning techniques and algorithms, and experience with common data science toolkits.
- Strong verbal and written communication skills.
- Curiosity, ownership and willingness to work in a collaborative environment
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 GS.com/careers.
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html
© The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
