Machine Learning Engineer, Senior Manager
Credit AcceptanceAbout the role
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. Our 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!
Outcomes and Activities:
- This position will work from home; occasional planned travel to an assigned Southfield, Michigan office location may be required. However, this position is permitted to work at a Southfield, Michigan office location if requested by the team member
- 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, an
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