
2026 Asset Wealth Management Machine Learning Engineer - Summer Associate
Alumni · Jersey City, NJ, United States
Weak hiring record · median 174 days open
All reasons
- Open 153 days
- This role has been posted 3 times
- 89% of this employer's openings are over 60 days old
- The same description appears on 30 of this employer's postings
In its favour
- Still listed on the employer's own board
- Publishes a salary range
Join our team as an ML Engineer Intern to help reimagine Private Banking by developing advanced AI agents and impactful machine learning solutions. Collaborate across business lines to research, build, and deploy innovative agents. Make a real impact by transforming client experiences with the latest AI technologies.
As an Asset Wealth Management Machine Learning Engineer - Summer Associate, you will apply advanced NLP, LLM, and AI techniques to generate actionable insights from large-scale financial data. Work with industry experts to design scalable data pipelines and support data-driven investment decisions. Empower automation and innovation on our cutting-edge investment platform.
Job responsibilities
- Design, deploy and manage prompt-based models on LLMs for various NLP tasks in the financial services domain
- Conduct research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
- Build comprehensive testing setups to evaluate model performance and ensure efficacy and reliability.
- Collaborate with engineering teams to deliver high-quality, scalable solutions.
- Study scientific articles and research papers to identify emerging techniques and discover new approaches.
Required qualifications, capabilities, and skills
- Advanced degree in Data Science, Computer Science, or Machine Learning.
- Proven experience in natural language processing and working with large language models.
- Proficiency in programming languages such as Python and familiarity with machine learning libraries and frameworks.
- Excellent communication skills and ability to work collaboratively in a fast-paced, dynamic environment.
- Strong analytical skills with an understanding of financial markets and asset management.
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