Description:

We have an exciting and rewarding opportunity for software engineers to advance their careers within the AI/ML & Data Platform team at JPMorganChase. As an Applied AI ML Associate Senior, you will be a seasoned member of an agile team, responsible for designing and delivering trusted, secure, and scalable technology products that support the firm's business objectives.

You will execute software solutions, develop production-ready, secure, and high-quality code, and maintain algorithms that interact with various systems. Your role includes producing architecture and design artifacts for complex applications and gathering and analyzing large datasets to improve software systems continuously.

Critical responsibilities include identifying hidden problems in data, driving improvements in code quality and system architecture, contributing to communities of practice exploring emerging technologies, and promoting a culture of diversity, inclusion, and respect.

Key Technical Skills:

Python, AI/ML concepts, Natural Language Processing (NLP), Large Language Models (LLMs), Deep Learning frameworks (PyTorch, TensorFlow), GPU Optimization, Finetuning, Embedding Models, Inferencing, Prompt Engineering, Retrieval-Augmented Generation (RAG), Machine Learning frameworks (MLFlow, Ray), Cloud platforms (AWS, Sagemaker, EKS), Data Structures, Algorithms, Data Mining, Statistics

Requirements:

• Formal training or certification in applied AI/ML concepts
• Minimum 3 years of applied experience in AI/ML
• Hands-on programming experience primarily with Python
• Practical application of data science and machine learning techniques to business challenges
• Strong background in NLP and LLMs
• Expertise in deep learning frameworks including PyTorch and TensorFlow
• Ability to work independently with minimal supervision
• Excellent communication and teamwork skills, with leadership in collaboration
• Preferred: Experience with distributed training frameworks (Ray, MLFlow), advanced AI/ML methodologies (search/ranking, recommender systems, graph techniques), reinforcement/meta learning, cloud deployment experience, and advanced LLM techniques (agents, planning, reasoning)