Staff Machine Learning Engineer

The ML/AI team at Credit Acceptance is a part of our Engineering team, which has a mission to bring innovation and modernization to the auto-lending industry. As a Senior Staff / Staff MLE at Credit Acceptance, you will play a pivotal role in the success of this mission as you would lead the development of AI-powered solutions across different business areas. This involves understanding the business processes, identifying new opportunities to add value using ML/AI algorithms and harnessing data sources to build state-of-the-art ML/AI solutions.

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
• Architect and implement enterprise-grade LLM-powered solutions, managing the full lifecycle from business requirements to production deployment, monitoring, and continuous optimization
• Design and develop multi-agent GenAI systems using state-of-the-art frameworks (LangChain, LlamaIndex) to orchestrate complex workflows across retrieval augmentation, data operations, and compliance verification
• Engineer robust Retrieval Augmented Generation (RAG) pipelines incorporating advanced techniques such as hybrid retrieval, reranking, query expansion, and contextual compression
• Implement parameter-efficient fine-tuning strategies (LoRA, QLoRA, PEFT) to adapt foundation models to domain-specific use cases while optimizing for inference costs and latency
• Develop intelligent routing and orchestration systems to manage conversation state across multiple specialized AI agents, ensuring seamless transitions between different system capabilities
• Build evaluation frameworks to measure and improve LLM performance across diverse metrics including factuality, coherence, task completion, and alignment with business objectives
• Integrate LLM solutions with existing enterprise architecture, ensuring compliance with data security policies, authentication mechanisms, and transaction safety requirements

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 relevant technical field with at least 3+ years of relevant experience or MS with at least 5+ years of experience 
• 6+ years of experience building and deploying Deep Learning models including Reinforcement algorithms, Recommendation systems, etc. with solid understanding of the mathematics, advanced statistics and engineering behind building such infra 
• Hands-on experience with building, fine-tuning and deploying multi-modal LLM Models and managing the end-to-end model lifecycle
• Experience partnering with the engineering, product, BizOps and other data teams while designing, building and executing solutions 
• Deep understanding in at least three of the following areas: data mining, advanced statistics, machine learning, NLP or computer vision 
• Strong problem solving with bias for action 

Preferred:

• Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies
• Experience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray)
• Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints

Target Compensation: A competitive base salary range from $153,759 - $225,514. This position is eligible for an annual variable bonus of cash and equity, between 10-20%. Final compensation within the range is influenced by many factors including 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. 

INDENGLP

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Benefits

• Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/ dental/vision and many nonstandard benefits that make us a Great Place to Work 

Our Company Values:

To be successful in this role, Team Members need to be:

• Positive by maintaining resiliency and focusing on solutions
• Respectful by collaborating and actively listening
• Insightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions
• Direct by effectively communicating and conveying courage
• Earnest by taking accountability, applying feedback and effectively planning and priority setting

Expectations:

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

Advice!

We understand that your career search may look different than others. Our hiring team wants to make sure that this would be a fit not just for us, but for you long term.  If you are actively looking or starting to explore new opportunities, send us your application!

P.S.

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