Applied AI ML Engineer Lead

JPMorganChase; Palo Alto (CA); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Comprehensive health care coverage

Retirement savings plan

Tuition reimbursement

Mental health support

Job summary

JPMorganChase is looking for a Lead in Applied Artificial Intelligence and Machine Learning in Palo Alto. This role will architect and deliver AI solutions to automate operations, mentoring engineers while collaborating with various teams.

Successful candidates will have 5+ years of experience, preferably with advanced degrees in technical fields. The position offers a competitive salary and a comprehensive benefits package.

Qualifications

• 5 or more years of applied experience in AI and Machine Learning.
• Demonstrated experience designing experiments for machine learning systems.
• Proven track record deploying machine learning applications into production.

Responsibilities

• Deliver generative AI and agent-based solutions for complex workflows.
• Translate business problems into research and engineering plans.
• Mentor and develop applied AI engineers and researchers.

Skills

Applied artificial intelligence and machine learning concepts

Software engineering skills in modern programming languages

Experience with distributed computing patterns

Ability to lead through influence

Education

Advanced degree (Master's or Doctorate) in Computer Science, Machine Learning, Statistics

Tools

Machine learning frameworks

AWS SageMaker

Amazon Bedrock

Job description

Applied Artificial Intelligence and Machine Learning Lead

Our goal is to build the next generation of AI: autonomous agents that can reason, plan, act, and learn to solve critical problems for an industry leading financial institution. The Applied Artificial Intelligence and Machine Learning team in Commercial and Investment Banking is transforming operations by leveraging the latest advancements in agentic AI and frontier models.

Responsibilities

• Architect and deliver generative artificial intelligence and agent-based solutions that automate complex operational workflows end-to-end.
• Translate priority business problems into research and engineering plans, success metrics, and scalable solution designs.
• Build multi-agent systems that collaborate reliably, coordinate tasks, and improve over time through feedback and evaluation.
• Design reusable services, libraries, and reference architectures that accelerate adoption across applied AI teams.
• Establish rigorous experimentation practices, including offline/online evaluation, ablation testing, and error analysis, to drive measurable improvements.
• Mentor and develop applied AI engineers and researchers, fostering a culture of scientific rigor, ownership, and continuous learning.
• Partner with stakeholders across business and technology teams to scale solutions responsibly, balancing performance, reliability, and security.

Required Qualifications

• Formal training or certification on applied artificial intelligence and machine learning concepts and five or more years of applied experience.
• Advanced degree (Master's or Doctorate) in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• Demonstrated experience designing experiments and evaluations for machine learning systems, including clear metrics and reproducible results.
• Proven track record deploying machine learning applications into production environments with operational excellence (monitoring, reliability, and lifecycle management).
• Strong software engineering skills in modern programming languages and machine learning frameworks, with experience building reusable components.
• Experience with distributed computing patterns for training and serving, and with state management for agent workflows.
• Ability to lead through influence across cross‑functional teams, translating complex technical topics for varied audiences.

Preferred Qualifications

• Experience building and evaluating autonomous agent systems (planning, tool‑use, orchestration, and multi‑agent coordination).
• Experience with cloud‑based machine learning platforms, such as Amazon Web Services SageMaker or Amazon Bedrock.
• Publications, open‑source contributions, or other evidence of applied research impact in machine learning or generative artificial intelligence.
• Familiarity with financial services domains and operational processes, including risk‑aware design and production constraints.

Federal Deposit Insurance Act

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorgan Chase’s review of criminal conviction history, including pretrial diversions or program entries.

Benefits

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. 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 provide a range of benefits and programs to meet employee needs, including comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching.

Equal Opportunity Employer

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans. 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.