Applied AI ML Associate

JPMorgan Chase; Jersey City (NJ); On-site; USD 120,000 - 160,000; Full time

Job summary

JPMorganChase in Jersey City is seeking an Applied AI ML Associate to design, develop, and productionize ML and DL solutions, including generative AI use cases. You will collaborate with product and engineering teams to translate business needs into reliable models, workflows, and platform capabilities.

You will contribute to a scalable ML platform supporting multiple business lines while maintaining performance, quality, and usability standards.

Qualifications

• MS/PhD in Computer Science, Machine Learning, or related field.
• 2+ years of applied ML experience.
• Strong Python proficiency and ML/DL fundamentals.
• Solid NLP and LLM knowledge.
• Hands-on ML/DL, with PyTorch or TensorFlow.

Responsibilities

• Serves as SME on a wide range of ML techniques and optimizations.
• Provides in-depth knowledge of ML algorithms, frameworks, and techniques.
• Enhances ML workflows with proficiency in LLMs and related techniques.
• Conducts experiments, analyzes results, and tunes models.
• Hands-on coding to productionize results in Python for POC and production solutions.
• Optimizes system accuracy and performance by addressing inefficiencies and bottlenecks.
• Integrates Generative AI within the ML Platform using state-of-the-art techniques.

Skills

Python

NLP

LLMs

Deep Learning

PyTorch

TensorFlow

GPU optimization

Model deployment

Experimentation

Communication

Education

MS/PhD in Computer Science or related field

2+ years applied ML experience

Tools

PyTorch

TensorFlow

AWS SageMaker

Ray

MLFlow

Job description

Bring your applied research and machine learning skills to a team building modern, high-impact generative AI capabilities. You'll work in a collaborative environment where experimentation, engineering excellence, and customer focus come together to deliver real outcomes.

As an Applied AI ML Associate at JPMorganChase within the Applied Artificial Intelligence and Machine Learning Data Platforms team in Corporate Sector, you will help design, develop, and productionize machine learning and deep learning solutions, including generative AI use cases. You will partner closely with product and engineering stakeholders to turn business needs into reliable models, workflows, and platform capabilities. You will contribute to a scalable platform approach that can support multiple business lines while maintaining strong standards for performance, quality, and usability.

Job responsibilities

• Serves as a subject matter expert on a wide range of ML techniques and optimizations.
• Provides in-depth knowledge of ML algorithms, frameworks, and techniques.
• Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
• Conducts experiments using latest ML technologies, analyzing results, tuning models
• Provides has Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions.
• Optimizes system accuracy and performance by identifying and resolving inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions.
• Integrates Generative AI within the ML Platform using state-of-the-art techniques.

Required qualifications, capabilities, and skills

• MS and/or PhD in Computer Science, Machine Learning, or a related field, with at least 2 years of applied machine learning experience.
• Experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must.
• Experience in applying data science, ML techniques to solve business problems.
• Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs)
• Hands‑on experience with machine learning and deep learning methods.
• Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow.
• Experience in advanced applied ML areas such as GPU optimization, fine tuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search).
• Ability to work on tasks and projects through to completion with limited supervision.
• Passion for detail and follow through. Excellent communication skills and team player

Preferred qualifications, capabilities, and skills

• Master's degree in computer science, ML or related areas
• Experience with Ray, MLFlow, and/or other distributed training frameworks.
• In‑depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
• Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
• Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.
• Experience working with large-scale MLOps pipelines, working with and deploying models to production services.