135 Best machine learning engineer Jobs in Atlanta, Georgia (October 2025)

Credit Acceptance Corporation

Machine Learning Engineer, Senior Manager

9 days ago

Atlanta

Credit Acceptance is proud to be an award-winning company with local and national workplace recognition in multiple categories! Our world-class culture is shaped by dedicated Team Members who share a drive to succeed as professionals and together as a company. A great product, amazing people and our stable financial history have made us one of the largest used car finance companies nationally. 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! We are seeking a highly motivated and experienced Leader of ML and AI Engineering within the AI team. The ideal candidate will have a strong technical background in decision science, machine learning, and generative AI with a proven track record in solving business problems and implementing large-scale automated solutions in partnership with the respective engineering teams. The leader will partner with business and engineering stakeholders to formulate the vision to achieve the company’s strategic goals and co-lead the roadmap to deliver innovative solutions for dealers, consumers, and team members. As a Senior Manager, MLE at Credit Acceptance, you will play a pivotal role in the success of this mission as you will 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: • 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, • 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., • 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, • 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 experimentation and visualization techniques., • 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, • Experience with Databricks MLflow for ML lifecycle management and model versioning, • Hands-on experience with Databricks Model Serving for production ML deployments, • Proficiency with GenAI frameworks/tools and technologies such as Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, and Databricks., • Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models, • 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 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 #zip #LI-Remote Benefits 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. We have great details around our stats, success, history and more. We’re proud of our culture and are happy to share why – let’s talk! Required degrees must have been earned at institutions of Higher Education which are accredited by the Council for Higher Education Accreditation or equivalent. Credit Acceptance is dedicated to providing a safe and inclusive working environment for all. As part of our Culture of Compliance, we are proud to be an Equal Opportunity Employer and value our culturally diverse workforce. All qualified applicants will receive consideration for employment regardless of the person’s age, race, color, religion, sex, gender, sexual orientation, gender identity, national origin, veteran or disability status, criminal history, or any other legally protected characteristic. California Residents: Please click ___ for the California Consumer Privacy Act (CCPA) notice regarding the personal information Credit Acceptance may collect from you. Play the video below to learn more about our Company culture.

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