Software Engineer III Data Analytics

We 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 Corporate Technology Infrastructure Management team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading 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. You should have sound understanding of Machine Learning, LLM , and Artificial Intelligence & generative AIs within Infrastructure (compute, shared clusters, Infra life cycle management etc)

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
 Work with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.
 Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet automation needs.
 Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
 Implement optimization strategies to fine-tune generative models for specific NLP use cases, ensuring high-quality outputs in summarization and text generation.
 Conduct thorough evaluations of generative models (e.g., GPT-4), iterate on RAG architectures, and implement improvements to enhance overall performance RAG applications
 Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
 Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
 Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.

Required qualifications, capabilities, and skills
 Formal training or certification on software engineering concepts and 3+ years applied experience
 7+ years of experience delivering products, projects, technology applications with experience managing technical platforms infrastructure and/or data-focused capabilities.
 Formal training or certification on software engineering concepts and 5+ years of applied experience.
 Experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
 Proficient in programming languages like Python for model development, experimentation, and integration with OpenAI API.
 Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
 Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
 Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
 Knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
 Good understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning).
 Proficient in identifying and addressing AI/ML/LLM/GenAI challenges, implement optimizations and fine-tune models for optimal performance in NLP applications.

Preferred qualifications, capabilities, and skills
 Familiarity with modern front-end technologies
 Familiarity with the financial services industries infrastructure / cloud .,