Lead Software Engineer - GenAI / ML

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Wealth Management - Applied AI & Analytics team, you play a crucial role in an agile team dedicated to enhancing, building, and delivering market-leading technology products that are secure, stable, and scalable. You are a key technical contributor responsible for implementing critical technology solutions across various technical domains to support the firm's business objectives. Our team leverages cutting-edge machine learning techniques alongside the company's unique data assets to optimize business decisions. In this position, you will be part of our industry-leading data analytics team, advancing financial applications from business intelligence generation to predictive models and automated decision-making. You will collaborate closely with financial advisors, investors, client service, and operations.

Job 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.
• Communicates final results and give context.
• Documents approach and techniques used.
• Works on longer term projects, building tooling that can be used to scale certain types of analyses across multiple datasets and business use cases.
• Collaborates with internal machine learning teams.
  

Required qualifications, capabilities, and skills

• 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
• 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.
• 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.
  

Preferred qualifications, capabilities, and skills

• PhD In a quantitative discipline