JPMorgan Senior Lead Software Engineer AI/ML 

United States, New Jersey, Jersey City 

135178902

Job Responsibilities

• Collaborate with product managers, data scientists, and software engineers to understand business requirements and translate them into technical solutions.
• Design, develop, and deploy scalable platform applications for payment technologies.
• Optimize and maintain existing AI/ML models to improve performance and accuracy.
• Conduct data analysis and preprocessing to ensure high-quality input for model training.
• Manage project prioritization and leading regular technology meetings with different stake holders
• Participate in code reviews and contribute to a culture of continuous improvement and innovation.
• Provide technical guidance and mentorship to global team members.

Required qualifications, capabilities, and skills

• Formal training or certification on Computer Science, Engineering, Mathematics concepts and 5+ years applied experience
• Proven experience as an AI/ML Engineer or similar role, with a strong portfolio of successfully deployed models.
• Proficiency in programming languages such as Python, R, or Java, with a focus on AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with data processing and analysis tools (e.g., Pandas, NumPy, SQL).
• Proficiency with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for deploying AI/ML solutions.
• Strong understanding of machine learning algorithms, data structures, and software design principles.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred qualifications, capabilities, and skills

• Experience in the Investment banking industry, particularly in payments technology.
• Familiarity in Java full stack and DevOps practices and tools for continuous integration and deployment.
• Experience with big data technologies (e.g., Hadoop, Spark) and real-time data processing.