JPMorgan Chase's Wealth Management - Applied AI & Analytics team is looking to enhance, build, and deliver market-leading technology products that are secure, stable, and scalable by leveraging cutting-edge machine learning techniques and company data assets to optimize business decisions, advancing financial applications from business intelligence generation to predictive models and automated decision-making.
Requirements
- Experience with machine learning APIs and computational packages (examples: TensorFlow, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels).
- Strong ability to develop and debug in Python or similar professional programming language.
- Experience with big-data technologies and platforms such as Spark, Snowflake, etc.
- Background and experience in language model fine-tuning and building language models from scratch.
- Experience with common Generative AI software stack (i.e. HuggingFace, LangChain, FAISS, DSPy, etc.)
- Must have the ability to design or evaluate intrinsic and extrinsic metrics of your model’s performance which are aligned with business goals.
- Must be able to independently research and propose alternatives with some guidance as to problem relevance.
Responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Develops secure high-quality production code, and reviews and debugs code written by others
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- Collaborates with business stakeholders to formulate relevant financial and business questions that can be answered by data analysis.
- Research's and analyzes data sets using a variety of statistical and machine learning techniques.
Other
- Formal training or certification on software engineering concepts and 5+ years applied experience
- B.S. or M.S. in a quantitative discipline in Computer Science, Mathematics, Statistics, Engineering, Data Science or similar
- Must be able to undertake basic and advanced EDA, may require some direction from more senior team; should be aware of limitation and implication of methodology choices.
- Ensures re-use and sharing of ideas within team and locale.
- Able to work with non-specialists in a partnership model, conveys information clearly and creates a sense of trust with stakeholders.
