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Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity apply your skills and have a direct impact on global business. You will be building production-grade ML services, developing end-to-end ML pipelines, and collaborating to develop large-scale data modeling experiments. Your expertise in Python, PySpark, DL frameworks like TensorFlow, and MLOps will be crucial in this role.
As a Machine Learning Lead Software Engineer at JPMorgan Chase within the Corporate Oversight and Governance Technology AI/ML 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 firm’s business objectives.
Job responsibilities
* Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases.
* Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet business objectives.
* Manage, mentor, and guide a team of ML and MLOps engineers.
* 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 (., GPT-4.1), iterate on model architectures, and implement improvements to enhance overall performance in NLP 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 Python and AI/ML engineering concepts and proficient advanced experience
* Bachelor's or Master's degree in Computer Science, Engineering, or a related field
* Demonstrated experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
* Proficiency 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.
* Experience with cloud computing platforms (., AWS, Azure, or Google Cloud Platform), containerization technologies (., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
* Solid understanding of fundamentals of statistics, machine learning (., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs.
* Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations and fine-tune models for optimal performance in NLP applications.
* Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
* A portfolio showcasing successful applications of generative models in NLP projects, including examples of utilizing OpenAI APIs for prompt engineering.
Preferred qualifications, capabilities, and skills
* Familiarity with the financial services industries.
* Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
* Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
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