# Machine Learning Engineer, Senior Manager Source: https://realanalystjobs.com/job/machine-learning-engineer-senior-manager-credit-acceptance-095b191c Machine Learning Engineer, Senior Manager at Credit Acceptance, an on-site role based in San Francisco Bay Area, California, USA. Posted on 26 October 2026, read from Credit Acceptance's own careers page (Workday), which RealAnalystJobs re-checks daily and removes the role when it closes. Updated 15 November 2026. ## Key facts - Company: [Credit Acceptance](https://realanalystjobs.com/companies/credit-acceptance) - Location: San Francisco Bay Area, California, USA - Work mode: On-site - Posted: Oct 26, 2026 - Employment type: Full time - Source: Credit Acceptance's careers page (Workday), re-checked daily Skills: Snowflake, Airflow ## About this role At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Outcomes and Activities: • Lead the vision and the strategic execution with a strong focus on continuous and long-term value creation across all participants of our flywheel • Collaborate with management and stakeholders to define strategic roadmaps and translate them into actionable quarterly plans. • Drive execution and delivery of ML/AI solutions by managing priorities, deadlines, and deliverables, leveraging your technical expertise. • Design and deliver scalable, secure systems using state-of-the-art AI/ML technologies and industry best practices, and nurture the culture of creating high-quality, well-tested systems to address critical product and business needs. • Troubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency. • Ensure the security, scalability, and architectural integrity of feature designs through reviews across teams. • Deliver hands-on solutions while mentoring other data professionals (including MLEs) within the organization • Explore and apply advanced machine learning techniques, including large language models (LLMs), deep learning, and graph neural networks, to solve complex challenges across the organization. • Guide a team of MLEs across different areas: • Mentoring: Mentor team members on design principles, coding standards, and the adoption of AI productivity tools. • Recommendations - Personalize guidance across different surfaces using deep learning methods; personalize layouts with Bayesian contextual multi-armed bandits • Growth: Foster long-term growth through data-driven causality and incrementality • Gen-AI: Power existing applications with Gen AI models and engineering to improve downstream experience and decisions • Lifecycle - Using ML models (such as XGBoost & Causal Meta-Learner-based model, etc), proactively guide business teams across different areas • Engineering - With engineering partners, build ML and Gen-AI platform and inference pipelines for different types of models Competencies: The following items detail how you will be successful in this role. • Customer Empathy: Customer Empathy is the 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: Engineering Excellence is about 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 One Team mindset refers to 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. This enables teams to navigate challenges and pursue shared objectives more effectively. • Owner’s Mindset: Owner’s Mindset involves adopting a set of behaviors that reflect a sense of 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: • PhD in Computer Science, Stats, Economics, or a relevant technical field with at least 8+ years of relevant experience or MS with at least 10+ years of experience in machine learning and software engineering • 8+ years of hands-on experience designing, building and deploying AI (ML, DL, Gen-AI) models, including Reinforcement Learning algorithms, Recommendation systems, Transformers, fine-tuned LLMs, Regressions, etc., with a solid understanding of mathematics, statistics, and engineering needed to build such infrastructure • Hands-on expertise in scaling and maintaining production-grade ML services, with a strong focus on ML/LLM Operations (versioning, automation, observability, automated training and monitoring, etc.) and ability to balance ML model complexity with production requirements • Passion for identifying new business opportunities and experience of using a test and learn approach to bring scalable and efficient solutions integrating AI algorithms, ML/LLM Ops, and s/w engineering • Experience partnering with the engineering, product, business operations, legal and other teams while designing, building, and executing solutions • Strong problem-solving skills with bias for action • Candidates must reside in or be willing to relocate to one of the following hub locations: the greater Southfield, Michigan, area; the greater Bellevue, Washington, area; or the San Francisco Bay Area, California. Preferred • Experience in automative industry, especially in building ML/AI systems while ensuring local and central regulations • Experience in model interpretability and responsible AI practices. • Expertise in data science, advanced experi Description from Credit Acceptance's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/machine-learning-engineer-senior-manager-credit-acceptance-095b191c) and use Apply now there to reach the employer's application. The listing is re-checked against Credit Acceptance's careers page daily and removed when it closes. ## Credit Acceptance Analyst roles on Real Analyst Jobs. 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