Lead Software Engineer - AI/ML

Job Description
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 Consumer and Community Banking - CAMP Technology , 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. You will play a key role as an experienced member of our global team. Your responsibilities will include business problems through data analysis, building cutting edge ML and LLM models, and deploying and supporting production grade models on AWS or Azure addressing.
Job responsibilities

• Responsible for setting direction, development, and implementation of ML and GenAI driven solutions
• Develop and implement machine learning models and algorithms to solve complex business and operational use cases.
• Design and deploy generative AI applications to automate and optimize business processes.
• Conduct research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
• Analyze large datasets to extract actionable insights and drive data-driven decision-making.
• Ensure the scalability and reliability of AI/ML solutions in a production environment.
• Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization
• Communicate findings and insights to stakeholders through presentations, reports, and visualizations.
• Stay up-to-date with the latest advancements in AI/ML technologies and integrate them into our operations.
• Mentor and guide junior team members in AI/ML best practices and methodologies.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Proven experience in deploying AI/ML applications in a production environment, with skills in deploying models on AWS platforms such as SageMaker or Bedrock.
• Familiarity with MLOps practices, encompassing the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
• Hands on experience in machine learning frameworks such as TensorFlow, PyTorch, Pytorch Lightning, or Scikit-learn.
• Proficiency in programming languages such as Python, Java etc.
• Proficiency in writing comprehensive test cases, with a strong emphasis on using testing frameworks such as pytest to ensure code quality and reliability.
• Experience with generative AI models, including GANs, VAEs, or transformers.
• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes, Amazon EKS).
• Excellent problem-solving skills and the ability to work independently and collaboratively.

Preferred qualifications, capabilities, and skills

• Experience in using GenAI (OpenAI or AWS Bedrock) to solve business problem.
• Experience with large scale training, validation and testing
• Experience fine-tuning LLMs with approaches like LoRA, QLoRA, and DoRA.
• Solid understanding of AI/ML algorithms and techniques, including deep learning, reinforcement learning, and natural language processing (NLP).
• Familiarity with AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, and Keras , as well as LLM frameworks, such as LangChain, LangGraph, etc.
• Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
• Expert knowledge of one of the cloud computing platforms preferred: Amazon Web Services (AWS), Azure, Kubernetes.