Applied AI ML Associate Senior
Aumni
Job Responsibilities
- Provide technical guidance and direction to business units, engineering teams, contractors, and vendors.
- Serve as a subject matter expert in AI, machine learning, and related technologies.
- Advise executive leadership with strategic recommendations on machine learning initiatives.
- Design, develop, and maintain secure, high-quality production code.
- Review and debug code to ensure adherence to best practices and code quality.
- Champion software and model quality, integrity, and security across the organization.
- Influence product design, application functionality, and technical operations.
- Architect and oversee the development of advanced machine learning models and systems using cutting-edge technologies.
- Ensure platforms support complex use cases, including real-time predictions, big data processing, and advanced analytics.
- Drive innovation in machine learning, ensuring solutions are scalable, flexible, and future-proof.
- Advocate for firmwide frameworks, tools, and SDLC best practices within the engineering community.
Required Qualifications, Capabilities, and Skills
- Formal training or certification in software engineering concepts with 3+ years of applied experience.
- Proven technical leadership and experience guiding engineering teams.
- Expertise in developing, reviewing, and debugging secure, high-quality production code.
- Deep knowledge of machine learning, big data processing, and advanced analytics.
- Experience architecting scalable and flexible machine learning platforms.
- Demonstrated ability to drive innovation and influence technology adoption.
- Excellent communication skills, with the ability to advise and influence executive leadership.
- Technical proficiency in Python for software and model development, AWS Cloud for scalable solution deployment. Retrieval-Augmented Generation (RAG) and AI/Agents, Natural Language Understanding (NLU), Natural Language Processing (NLP), and Large Language Models (LLM)
- Experience with engineering and operational best practices ML Ops for operationalizing machine learning workflows, CI/CD pipelines for continuous integration and delivery, SDLC best practices for software development lifecycle management
Preferred Qualifications, Capabilities, and Skills
- Experience in the financial services industry, especially in consumer and community banking.
- Familiarity with firmwide frameworks, tools, and SDLC best practices.
- Track record of contributing to the engineering community and promoting best practices.
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
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.
Lead the design and delivery of advanced AI and machine learning solutions, shaping the future of banking at JPMorgan Chase.