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About This Role
JOB DESCRIPTION
Join Chase Auto, a leader in auto financing with over $85 billion in assets and partnerships with 75% of U.S. franchised automotive dealers. As part of the prestigious JP Morgan Chase franchise, we serve vehicle manufacturers, auto dealers, and consumers with a comprehensive suite of financial products and services, from retail lending and captive financing to commercial services like floorplan products, treasury services including deposits, cash management, and payment processing.
The Head of Retail \& Consumer Marketing will oversee a team responsible for the strategy, planning, and execution of both direct\-to\-consumer (B2C) and indirect dealer retail (B2B) segments. The successful candidate will lead development of integrated go\-to\-market strategies and programs to unlock growth and synergies between the indirect retail and direct\-to\-consumer car buying and financing audiences and channels. Demonstrative knowledge and experience in creating and capturing demand across the customer journey is key.
Key Responsibilities:
- Strategic Marketing Plans: Develop and implement strategic marketing plans to support the growth and expansion of the dealer network and consumer originations acquisition via prospecting to drive more through the door applications across the Chase dealer network, ensuring alignment with business goals. Oversee owned, earned and paid media in support.
- Brand Strategy: Implement visual identity and brand voice for Chase Auto retail and consumer segments. Lead brand creative and expression in the marketplace to enhance brand recognition and loyalty.
- Sales Enablement: Support the geographic sales force with marketing content, pitch materials, and lead capture and nurturing.
- Segmentation: Maintain dealer segmentation and curate the client database of contacts across the dealer network to ensure targeted and effective marketing efforts. Continue to mature consumer segmentation and consumer buyer persona insights.
- Value Proposition: Maintain a pulse on competitor offerings in the marketplace and best position Chase Auto given its advantages. Partner with business leadership in leveraging feature / benefits mapping to further inform our value proposition, reasons to believe, and go\-to\-market messaging.
- Marketing Communications: Develop and maintain client and customer contact strategies using campaigns and always\-on communication of offerings and advisory leveraging Salesforce Marketing Cloud.
- Client Engagements \& Experiences: Lead and facilitate key client engagements requiring high\-touch, elevated, and exclusive experiences that deliver franchise value including live webinars or in\-person venue.
- Team Leadership: Lead and manage a marketing team, providing guidance, mentorship, and support to ensure the successful execution of marketing initiatives.
- Cross\-Department Collaboration: Collaborate with sales leadership, product, and other cross line of business teams including branch network to align marketing strategies with business goals and drive integrated solutions.
- Market Analysis \& Industry Trends: Analyze market trends and customer insights to identify opportunities for growth and innovation, informing strategic decisions and marketing initiatives. Stay up to date with industry trends and best practices, incorporating them into marketing strategies to maintain competitive advantage.
- Campaign Management: Oversee the creation and management of marketing campaigns, including digital marketing, events, and promotional activities, ensuring effective execution and impact.
- Performance Monitoring: Monitor and report on the effectiveness of marketing strategies and lead generation, using data\-driven insights to optimize performance and maximize ROI.
- Budget Management: Manage the marketing budget, ensuring efficient allocation of resources to maximize ROI and support strategic initiatives.
- Measurement \& Reporting: Establish KPIs and an overall success scorecard, including quantitative and qualitative metrics. Provide routine reporting and verbal presentations to senior leadership to track progress and inform decision\-making.
Qualifications:
- 10\+ years of leadership with demonstrative experience in development and implementation of B2B and B2C marketing strategies.
- Strong people leadership skills with experience managing and developing a team.
- Strong interpersonal skills with the ability to build relationships and influence stakeholders.
- Strong proficiency with executive\-level presentation materials and briefings, and the ability to simplify complex subject matter into digestible executive communications.
- Critical thinker with an analytical mindset to interpret data and make informed decisions.
- Creative thinker with a passion for innovation and continuous improvement.
- Exceptional written, presentation and verbal communication skills.
- Strong executive presence.
Preferred Qualifications:
- BS/BA degree required; MBA preferred.
- Auto industry expertise.
- Financial services experience.
- Proven experience in B2B marketing within a large enterprise and geographical sales teams.
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.
When it comes to buying a vehicle or refinancing an existing car loan, many customers turn to Chase to help. Our auto lending services are constantly evolving and incorporating the latest technology to help match car buyers with dealers, provide competitive financing options and ease loan management.
Salary Context
This $250K-$450K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At JPMorganChase, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Director-level AI roles across all categories have a median of $244,288. This role's midpoint ($350K) sits 110% above the category median. Disclosed range: $250K to $450K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
JPMorganChase AI Hiring
JPMorganChase has 192 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Data Scientist, AI Agent Developer. Positions span Columbus, OH, US, New York, NY, US, San Francisco, CA, US. Compensation range: $62K - $500K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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