Staff AIML Solutions Engineer

Credit Acceptance is proud to be an award-winning company recognized both locally and nationally across multiple workplace categories. Our world-class culture is shaped by dedicated team members who are driven to succeed as professionals individually and together as a team. Backed by a strong product, exceptional people, and a stable financial foundation, we’ve grown into a leading provider of used and new car financing across the country.

Our Engineering and Analytics Team Members utilize the latest technology to develop, monitor, and maintain complex practices that help optimize our success. Team Members value being challenged, are encouraged to express their ideas, and have the flexibility to enjoy work-life balance. We build intrinsic value by partnering with all functions of our business to support their success and make strategic business decisions. We focus on professional development and continuous improvement while enjoying a casual work environment and Great Place to Work culture.

About the role

The Staff AI/ML Solutions Engineer is a senior individual contributor within the AI/ML organization, accountable end-to-end for AI/ML products across the auto lending ecosystem—from the business problem and its prioritization through solution design, recommending build versus buy decisions, and realized value. This role operates at the intersection of business, product, engineering, and AI/ML, serving as the single point of contact to the business for assigned domains. The Staff AI/ML Solutions Engineer partners closely with stakeholders across Business Operations, ML Engineering, Platform Engineering, Data Science, AI Operations, Analytics, and Marketing.

This position is remote with occasional planned travel to an assigned Southfield, Michigan office location. Team members may also choose to work from the Southfield office if preferred.

Responsibilities

• Serve as the single point of contact to the business for assigned AI/ML domains; understand business needs, identify AI/ML opportunities, and define solution direction.
• Lead discovery: frame the business problem, size the opportunity, and validate the need and feasibility before committing to a solution.
• Own the product roadmap and its prioritization, making and demonstrating value in what the organization should and should not pursue.
• Define success in measurable terms, including KPIs, vision, and roadmap per product.
• Translate framed problems into clear solution direction, technical specifications, and delivery plans in partnership with AI/ML Engineering and AI/ML Science teams.
• Own the build-versus-buy recommendation for assigned solutions, with a defensible rationale; lead vendor evaluation, commercial input, integration design, and proof-of-concept scoping.
• Own the solution lifecycle from problem framing through delivery, adoption, and continuous improvement.
• Continually analyze operational signals from AI Operations (cost, quality, and usage) and translate them into the roadmap and re-solutioning work, including vendor renewal and true-up decisions.
• Establish, monitor, and analyze KPIs to evaluate effectiveness and drive iterative improvement.
• Act as a trusted advisor to business and technology leadership, influencing decisions through expertise, data, and clear communication, and protecting the roadmap from being captured by what is technically interesting rather than valuable.

Competencies

• Customer Empathy: Ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience.
• Engineering Excellence: Bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions.
• One Team: A collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication, and mutual support create a sense of collective purpose.
• Owner's Mindset: Adopting a set of behaviors that reflect responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Business, Data Science, Artificial Intelligence, Data Analytics, or a related field (Master's degree preferred).
• 8+ years of experience in technical product management, solution ownership, or business-facing solution roles, preferably within financial services, and including AI/ML or data products.
• Strong understanding of AI and machine learning concepts and system design, ability to set realistic expectations, and make defensible build-versus-buy decisions.
• Demonstrated ability to own a product outcome end-to-end, from problem framing through launch and post-launch monitoring.
• Working proficiency with Python, system design, and SQL sufficiently to engage credibly with technical teams and reason about feasibility.
• Strong understanding of AI features and capabilities including RAG, multi-agent systems, agentic AI, and LLM applications.
• Demonstrated ability to lead complex, cross-functional initiatives without formal people management responsibility.
• Excellent problem-solving, analytical, and stakeholder-communication skills, including the ability to communicate value and ROI to senior leadership.
• Comfortable operating with significant autonomy, accountability, and ambiguity.

Preferred Qualifications

• Experience defining metrics and KPI frameworks for AI/ML or data products.
• Experience implementing solutions using Databricks, MLflow, or the AWS technology stack.
• Experience owning vendor relationships, commercial negotiations, or integration design.
• Experience working in at least two of the following areas: Product, Data Science, Machine Learning, Data Engineering, Software Engineering.
• Strong working knowledge of Agile and Scrum methodologies.

Skills

• Ability to translate fuzzy business needs into both a measurable definition of success and a feasible solution shape.
• Strong systems thinking and ability to solve problems at the root cause with practical, scalable solutions.
• Strong prioritization skills and the ability to say no when required.
• Ability to communicate complex technical and analytical information clearly and concisely, both verbally and in writing, including to senior and executive leadership.
• Ability to build trust, credibility, and strong relationships across all levels of the organization.
• Proven ability to prioritize effectively and execute in a fast-paced, high-pressure environment.

Pay

A competitive base salary range from $153,760 – $225,514. This position is eligible for an annual variable bonus of cash and equity, between 10-20%, based on individual performance. Final compensation within the range is influenced by role-specific skills, depth and experience level, industry background, relevant education, and certifications. Candidates who reside in the following major metropolitan areas may be eligible for a premium on top of the posted range based on their specific zone: San Francisco, Seattle, Boston, New York City, Los Angeles, and San Diego.

Benefits

• Excellent benefits package including 401(K) match.
• Adoption assistance and parental leave.
• Tuition reimbursement.
• Comprehensive medical, dental, and vision coverage.
• Many nonstandard benefits that contribute to a Great Place to Work.

Company Values

To be successful in this role, team members need to be:

• Positive: Maintain resiliency and focus on solutions.
• Respectful: Collaborate and actively listen.
• Insightful: Cultivate innovation, accumulate business and role-specific knowledge, demonstrate self-awareness, and make quality decisions.
• Direct: Effectively communicate and convey courage.
• Earnest: Take accountability, apply feedback, and effectively plan and prioritize.

Expectations

• Remain compliant with our policies, processes, and legal guidelines.
• All other duties as assigned.
• Attendance as required by the department.