Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorganChase within the Commercial and Investment Bank Payments Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Adds to the team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Advanced in one or more programming language(s)
- Good working knowledge with PyTorch and Numpy
- Proficient in designing and building Transformer-based neural networks, including transfer learning and fine-tuning pre-trained models for downstream tasks
- Knowledge of regularization techniques (dropout, layer normalization, weight decay) to prevent overfitting
- Ability to design custom tokenization strategies and embedding layers suited to domain-specific data
- Good experience building ML models on timeseries datasets
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Understands the model deployment lifecycle (MLOps), including A/B testing and canary deployment strategies for model rollouts
- Familiarity with A/B testing and canary deployment strategies for model rollouts
Preferred qualifications, capabilities, and skills
- Good experience building ML models on timeseries datasets.
- Advanced in one or more programming language(s)
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field