DescriptionWe have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorgan Chase within the Commercial & Investment Bank you serve as a seasoned member of an agile team to design and deliver trusted marketleading technology products in a secure stable and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.
Job responsibilities
- Executes software solutions design development and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and highquality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers analyzes synthesizes and develops visualizations and reporting from large diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity equity inclusion and respect
Required qualifications capabilities and skills
- Formal training or certification onsoftware engineeringconcepts and 3 years applied experience
- Handson practical experience in system design application development testing and operational stability
- Proficient in programming languages such as Python along with experience in using machine learning frameworks like TensorFlow or PyTorch. Application development using Java Springboot and Relational database. Understanding of machine learning principles especially in natural language processing (NLP) and deep learning to effectively work with LLMs.
- Must have skills in data collection preprocessing and management to ensure highquality input data for training and finetuning models. DevOps and MLOps Experience in deploying and managing machine learning models in production environments including continuous integration and delivery (CI/CD) pipelines.
- Experience in developing debugging and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages. Ability to optimize models for performance and efficiency including techniques like quantization pruning and distillation.
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD Application Resiliency and Security. Understanding of data privacy security best practices and compliance requirements to ensure safe and ethical use of LLMs.
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g. cloud artificial intelligence machine learning mobile etc.. Knowledge of cloud platforms (e.g. AWS Google Cloud Azure) to leverage scalable storage and compute resources for model training and deployment.
Preferred qualifications capabilities and skills
- Familiarity with modern frontend technologies
- Exposure to cloud technologies