As an Applied ML and Generative AI leader within our Corporate Technology team, you will develop applications and provide tech support for all our corporate functions across our network. You will operate as a hands-on leader responsible for designing, building, and running production-grade ML and Generative AI services, while setting technical direction that scales across multiple workstreams. You will remain close to the code and architecture decisions, establish delivery and engineering standards, and ensure solutions meet enterprise expectations for security, stability, and operational rigor.
A core requirement is stakeholder partnership: you will routinely explain what is being built, why it matters, and how it will perform in production to both technical and non-technical audiences, enabling informed decisions and clear delivery alignment.
Job responsibilities
- Provide hands-on technical leadership by designing, developing, and deploying ML/LLM/GenAI solutions from concept through production, maintaining ownership for reliability and operability once deployed
- Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases.
- Mentor and uplift junior engineers through design reviews, code reviews, pairing, and coaching, raising engineering quality and delivery discipline across the team. You will build and institutionalize MLOps capabilities, including automated pipelines for deployment, monitoring, and model lifecycle management, with emphasis on scalability and reliability
- Implement optimization strategies to fine-tune generative models for specific NLP use cases, ensuring high-quality outputs in summarization and text generation.
- Conduct thorough evaluations of generative models (e.g., GPT-4.1), iterate on model architectures, and implement improvements to enhance overall performance in NLP applications.
- Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
- Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences. Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.
Required qualifications, capabilities, and skills
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field and 10+ years of engineering experience, including 3+ years building, deploying, and operating applied AI/ML systems in production (model lifecycle, MLOps, monitoring, and governance).
- Demonstrate hands-on engineering leadership: setting technical direction, making architecture decisions, conducting design and code reviews, mentoring junior engineers, and guiding implementation quality across multiple workstreams
- Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
- Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
- Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
- Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs.
- Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations and fine-tune models for optimal performance in NLP applications.
- A portfolio showcasing successful applications of generative models in NLP projects, including examples of utilizing OpenAI APIs for prompt engineering.
Preferred qualifications, capabilities, and skills
- Familiarity with the financial services industries.
- Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
- Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
- Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
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.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 10+ years of engineering experience
- 3+ years building, deploying, and operating applied AI/ML systems in production
- Experience with model lifecycle management, MLOps, monitoring, and governance
- Hands-on engineering leadership, including technical direction, architecture decisions, design reviews, code reviews, mentoring, and implementation guidance
- Proficiency in Python for model development, experimentation, and OpenAI API integration
- Experience with TensorFlow, PyTorch, Scikit-learn, and OpenAI API
- Experience with AWS, Azure, or Google Cloud Platform
- Experience with Docker, Kubernetes, microservices design, implementation, and performance optimization
- Understanding of statistics, machine learning, deep learning, reinforcement learning, and generative model architectures including GANs and VAEs
- Ability to optimize and fine-tune models for NLP applications
- Portfolio demonstrating successful generative-model NLP applications and OpenAI API prompt engineering
- Familiarity with the financial services industry
- Strong cross-functional collaboration and communication skills
- Expertise designing and implementing Retrieval-Augmented Generation pipelines
- Knowledge of Chain-of-Thoughts, Tree-of-Thoughts, and Graph-of-Thoughts prompting strategies
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical coverage and wellness resources, including mental-health support and wellness incentives, are described as comprehensive and accessible; feedback suggests income-based contributions help keep care affordable.
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Retirement Support — A dollar-for-dollar 401(k) match up to 5% of eligible pay, plus additional employer contributions in some cases, is highlighted as a strong pillar of financial security. Feedback suggests this structure is a notable advantage of the total rewards package.
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Parental & Family Support — Up to 16 weeks of paid parental leave for all parents, along with fertility, adoption, surrogacy, childcare, and family-support resources, signals a family-forward approach. Feedback suggests these programs are a standout feature of the package.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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