Credit Acceptance
Machine Learning Engineer, Senior Manager
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Senior Manager, Machine Learning Engineer (MLE) – AI & Decision Science
Location: Remote (with occasional travel to Southfield, MI or option for office basis) Salary Range: $184,354 – $270,386 Base + 15–30% variable cash/equity bonus (competition-based) Compensation premium for qualifying metro areas (SF, NY, LA, etc.)
About Credit Acceptance
Credit Acceptance is a nationally recognized leader in used and new auto financing, rooted in a Great Place to Work culture. Our AI team drives innovation by leveraging machine learning (ML), generative AI (Gen-AI), and cutting-edge analytics to optimize business processes and improve outcomes across dealer partnerships, consumer experiences, and internal systems.
About the Role: Purpose & Vision
We are seeking a tech-driven leader to shape Credit Acceptance’s long-term AI/ML strategy and drive the scientific and engineering capabilities of our Decision Science & AI Org. As Senior Manager, MLE, you will:
- Set the vision for high-impact ML/AI initiatives that create sustainable value for dealers, consumers, and internal teams.
- Collaborate with business, product, engineering, and legal teams to design, build, and deploy scalable AI solutions.
- Mentor cross-functional teams, align to strategic goals, and promote a culture of continuous improvement.
- Advance the frontiers of AI research while maintaining production-grade reliability, ethical practices, and responsible AI.
Key Responsibilities
1. Strategy & Leadership
- Partner with executive stakeholders to define and translate AI/ML roadmaps into actionable quarterly plans.
- Drive long-term value creation by evaluating emerging technologies (e.g., LLMs, LLMs Tune & Quantize, RNANs, Reinforcement Learning, causality/incrementality analysis) and aligning them to business goals.
- Lead AAI long-term flywheel vision, ensuring AI/ML solutions scale across all stakeholders.
2. Technical Leadership & Delivery
- Design and build production-ready AI systems using state-of-the-art MLOps tools (e.g., LightGBM, XGBoost, PyTorch, TensorFlow, scikit-learn, databases & large-scale cloud infrastructure).
- Optimize data pipelines, inference systems, and model lifecycle management with chaining, DAG-based deployment, and observability.
- Collaborate with platform engineering teams to extensibly build latest Gen-AI systems, reducing Takiya time and improving system acuity.
- Troubleshot and resolve complex scalability, reliability, and effectiveness issues.
3. AI Research & Applications
- Explore and deploy advanced ML/AI techniques:
- LLMs/Finetuning/Quantization (Chain-of-Thought, Tree-of-Thought)
- Model interpretability & responsible AI (causal inference, fairness audits, bias mitigation).
- Recommendation systems (Bayesian multi-armed bandits, context optimization).
- Alternative-Training (Finetune & Gen-AI) flow engineering.
- Innovate across data services pipelines (batch & streaming) and experimental designs to drive customer impact.
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4. Team Growth & Mentorship
- Mentor机ML/AI professionals (data scientists, engineers) on best practices, AI systems, coding standards, and tool adoption.
- Conduct peer reviews to ensure scalability, security, and technical excellence.
- Cultivate a knowledge-sharing culture by empowering underrepresented AI expertise.
5. Compliance & Accountability
- Ensure alignment with regulatory (especially automotive), ethical, reliability, and usability standards.
- Demonstrate organized ownership in fulfilling deliverables, deadlines, and role-expected behaviors.
Qualifications & Experience
Education & Experience
Minimum of:
- PhD in Computer Science, Statistics, Economics, or related field, or
- MS with 10+ years industry experience in ML Engineering, Data Science, or Software Engineering.
Technical Core
Essential:
- 8+ years hands-on experience in generative AI, deep learning, generative foundation models, recommendations, causal reasoning, reasoning by formation and Remuneration.
- Production-grade MLOps (versioning, scaling, observability, CI/CD, monitoring).
- Math/Stats expertise (regression, Bayesian inference, causal model tactics, optimization).
- Platform/Causal Engineering (e.g., Gauss/Hallsteininess, Epistemic Query against AI chip).
- Strong background in automotive or fintech domain (regulatory, risk-sensitive).
Advanced Specialization:
- Limited, Parameter Efficient Fine-Tuning (PET) & Quantization research experience (e.g., OFA, GraphLLM).
- Machine Learning Foundations & Deployment (XGBoost, Spark ML, Cuborbank Ray/A-AIC; Docker/Kubernetes).
- Dataflow and microservices (gRPC, GraphQL, Snowflake, Kafka, Airflow).
Leadership Traits & Collaborative Fit
- Solution-driven mindset: Motivated to identify growth topics and partner with tech/data/ecom layers.
- Bias toward action paired with creative problem-solving (e.g., prototyping, experimentation).
- Compassionate communication with ** engineers, PMs, and analysts**.
Credit Acceptance Culture, Expectations & Benefits
Our Culture: Diverse Growth & Inclusivity
- Respectful & Direct: Psst to robust feedback; solutions-oriented problem-solving.
- One Team: Full-stack cross-org collaboration and customer empathy.
- Defensive Excellence: Ownership + Ethical ownership capability across areas.
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Key Principles for Success
| Beckcamp | How You Accomplish It |
|---|---|
| Set Clear Expectations | Align stakeholders to team/company goals. |
| Enlist Owner’s Mindset | Thrive in accountability; take decisions on mission critical business areas. |
| Accountability (Accountability) | Quantify individual and team gain aligned with shared objectives. |
Compensation & Benefits
- Base Salary: $184,354 – $270,386
- Variable Bonus: 15–30% (equity included) based on role metrics.
- Premium potential (up to 5%+ acronym) for applicants in high-cost metro areas (SF, NYC, etc.).
- Flexible hybrid/RTO piece.
Perks
- Discounted auto financing options for credit acceptance team members.
- Cutting-edge technology & flexibility (using Git + CAD collaboration tools).
- Tuition impos Demand: Up to $10k/year (annual list options).
- Holidays + 27.5 PTO days (annually full-time).
- Medical/Health: Comprehensive – 100% PPO/preferred participation.
- Adverse options: Assisted Adoption benefits & RGCP BabyNutrition.
About Our Organization (In Short)
Why join Credit Acceptance?
- High impact: Your models get changed into dell or McLaren (and help millions).
- Climate: Aka Ideal employment, internal feedback, and car-Zoning our office policies.
- Research innovation: Authentic response with developers worldwide, coupled with responsible AI coding.
- Impact: Shapes AI behind deals/mechanisms online.
Equity Inclusion & Compliance
We foster an antequinal-noncompagin working environment, prioritizing diversity and multi-net in thought:
- Equal Opportunity Empleness
- CCPA Notice: California (Please click here for compliance attach). splendidly chains of PIO processing.
- AABCAP Investigated workplace and s{v}1dad vulnerabilities.
Ready to Make an Impact?
If you are addled for a new opportunity, apply today for full collaboration within this dynamic AI infrastructure—we’d love to hear from you!
Very soon, we are vested to hear evidences of learning and plans aligned to Automotive’s future!
Apply with your profile and CV here: [Credit Acceptance Careers] https://
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