Applied AI ML Lead - Sales Science

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Join our Sales Science Data and Analytics team and help us utilize AI and LLM tools to optimize banker and client engagement.
As an Applied AI ML Lead on the Sales Science team, you will contribute to innovative projects and drive the future of field AI Technologies, leveraging ML tools and algorithms to deliver the right solutions as we build interactive coaching tools for the firm. You will be part of an innovative team, working closely with business partners, product owners, and fellow data scientists to build new AI/ML solutions and productionlize them. We are looking for someone with a passion for data, ML, and programming, who can build ML solutions at-scale with a hands-on approach with detailed technical acumen.
Job responsibilities

• Serve as a subject matter expert on a wide range of ML techniques and optimizations.
  
   
• Build and enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
  
   
• Conducting experiments using latest ML technologies, analyzing results, tuning models.
  
   
• Actively engage in hands-on coding to convert experimental results into robust production solutions.
  
   
• Take full ownership of the entire code development lifecycle in Python, from proof of concept and experimentation to delivering production-ready solutions.
  
   
• Integrate Generative AI within the ML Platform using state-of-the-art techniques.
   

Required qualifications, capabilities, and skills

• Bachelor's degree with 7 years of applied machine learning experience.
  
   
• 5+ years of experience in one of the programming languages like Python, R, Java, 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)
  
   
• Experience with machine learning and deep learning methods.
  
   
• Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow
  
   
• 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

• In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
  
   
• MS and/or PhD in Computer Science, Machine Learning, or a related field, with at least 5 years of applied machine learning experience preferred.
  
   
• Advanced knowledge in Reinforcement Learning or Meta Learning.
  
   
• Software development experience is a plus.
  
   
• Demonstrated ability to translate LLM pipelines/workflows into something less technical business partners can understand.
  
   
• 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.

ABOUT US

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

ABOUT THE TEAM

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.