Senior Machine Learning Engineer, Manager

Credit Acceptance

. Lead the vision and strategic execution with a focus on continuous and long-term value creation .

Posted 10/23/2026full-timeUnited StatesSenior💰 $221,225 - $309,716 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying AI/ML solutions, with a strong focus on scalability, security, and operational efficiency. Proven ability to mentor teams and drive strategic execution while ensuring compliance with industry standards.

Highest-signal resume keywords

PhD In Computer Science, Stats, Economics, Or Relevant Field8+ Years Experience In Machine Learning And Software EngineeringHands-On Experience With AI/ML Models Including Reinforcement Learning And TransformersStrong Focus On ML/LLM Operations Including Automation And MonitoringExperience Partnering With Engineering And Business Operations Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningGenerative AIReinforcement LearningRecommendation SystemsTransformersXGBoostCausal Meta-LearnerStatistical AnalysisAI/ML Infrastructure Design

Soft Skills

Problem-SolvingMentoringCollaborationStrategic ThinkingCommunication

Tools & Technologies

ML ServicesAI Productivity ToolsInference PipelinesAutomated Training SystemsMonitoring Tools

Industry Keywords

AI/ML SolutionsScalabilitySecurityOperational EfficiencyComplianceData-Driven CausalityIncrementality

About the role

Key responsibilities & impact

Lead the vision and strategic execution with a focus on continuous and long-term value creation
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
Design and deliver scalable, secure systems using state-of-the-art AI/ML technologies and industry best practices
Nurture a culture of creating high-quality, well-tested systems for critical product and business needs
Troubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency
Ensure security, scalability, and architectural integrity through cross-team design reviews
Deliver hands-on solutions while mentoring data professionals, including MLEs
Explore and apply advanced machine learning techniques, including LLMs, deep learning, and graph neural networks
Guide a team of MLEs across recommendations, growth, generative AI, lifecycle, and engineering initiatives
Mentor team members on design principles, coding standards, and AI productivity tools
Personalize guidance using deep learning and personalize layouts with Bayesian contextual multi-armed bandits
Foster long-term growth through data-driven causality and incrementality
Power existing applications with Gen AI models and engineering
Proactively guide business teams using ML models such as XGBoost and Causal Meta-Learner-based models
Build ML and Gen-AI platforms and inference pipelines with engineering partners
Remain compliant with company policies, processes, and legal guidelines
Perform other duties as assigned

Requirements

What you’ll need

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.
Solid understanding of mathematics, statistics, and engineering needed to build AI/ML infrastructure
Hands-on expertise in scaling and maintaining production-grade ML services
Strong focus on ML/LLM Operations, including versioning, automation, observability, automated training and monitoring
Ability to balance ML model complexity with production requirements
Experience using a test and learn approach to bring scalable and efficient solutions integrating AI algorithms, ML/LLM Ops, and software engineering
Experience partnering with engineering, product, business operations, legal and other teams
Strong problem-solving skills with bias for action
Must reside in or be willing to relocate to the greater Southfield, Michigan area, greater Bellevue, Washington area, or San Francisco Bay Area, California
Required degrees must have been earned at institutions of Higher Education accredited by the Council for Higher Education Accreditation or equivalent

Benefits

Comp & perks

Annual variable incentive of cash and equity, between 15-30% of base salary
401(K) match
Adoption assistance
Parental leave
Tuition reimbursement
Comprehensive medical, dental, and vision benefits
Many nonstandard benefits
Hybrid work model with two work-from-home days per week