Machine Learning Engineer, Senior Manager

Credit Acceptance

United States

United States

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À propos

divh2Leader Of ML And Ai Engineering/h2pCredit 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./ppOur 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!/ppWe 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 companys strategic goals and co-lead the roadmap to deliver innovative solutions for dealers, consumers, and team members./ppAs 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./ph3Outcomes And Activities/h3ulliLead the vision and the strategic execution with a strong focus on continuous and long-term value creation across all participants of our flywheel/liliCollaborate with management and stakeholders to define strategic roadmaps and translate them into actionable quarterly plans./liliDrive execution and delivery of ML/AI solutions by managing priorities, deadlines, and deliverables, leveraging your technical expertise./liliDesign 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./liliTroubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency./liliEnsure the security, scalability, and architectural integrity of feature designs through reviews across teams./liliDeliver hands-on solutions while mentoring other data professionals (including MLEs) within the organization/liliExplore and apply advanced machine learning techniques, including large language models (LLMs), deep learning, and graph neural networks, to solve complex challenges across the organization./liliGuide a team of MLEs across different areas:/liulliMentoring: Mentor team members on design principles, coding standards, and the adoption of AI productivity tools./liliRecommendations Personalize guidance across different surfaces using deep learning methods; personalize layouts with Bayesian contextual multi-armed bandits/liliGrowth: Foster long-term growth through data-driven causality and incrementality/liliGen-AI: Power existing applications with Gen AI models and engineering to improve downstream experience and decisions/liliLifecycle - Using ML models (such as XGBoost Causal Meta-Learner-based model, etc), proactively guide business teams across different areas/liliEngineering - With engineering partners, build ML and Gen-AI platform and inference pipelines for different types of models/li/ul/ulh3Competencies/h3ullistrongCustomer Empathy:/strong Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customers shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience./lilistrongEngineering Excellence:/strong 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./lilistrongOne Team:/strong 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./lilistrongOwners Mindset:/strong Owners 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./li/ulh3Requirements/h3ulliHands-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/liliPassion 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/liliExperience partnering with the engineering, product, business operations, legal and other teams while designing, building, and executing solutions/liliStrong problem solving skills with bias for action/li/ulh3Preferred/h3ulliExperience in automative industry, especially in building ML/AI systems while ensuring local and central regulations/liliExperience in model interpretability and responsible AI practices./liliExpertise in data science, advanced experimentation and visualization techniques./liliExperience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray)/liliAbility to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints/liliExperience with Databricks MLflow for ML lifecycle management and model versioning/liliHands-on experience with Databricks Model Serving for production ML deployments/liliProficiency with GenAI frameworks/tools and technologies such as Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, and Databricks./liulliDemonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models/liliHands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies/li/ul/ulh3Knowledge And Skills/h3ulliPhD 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/lili8+ 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., with a solid understanding of mathematics, statistics, and engineering needed to build such infrastructure/li/ulh3Target Compensation/h3pA competitive base salary range from $184,354 $270,386. This position is eligible for an annual variable bonus of cash and equity, between 15-30%. Final compensation within the range is influenced by many factors including role-specific skills, depth and experience level, industry background, relevant education and certifications./ppCandidates 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./ph3Benefits/h3ulliExcellent 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/li/ulh3Our Company Values/h3ulliPositive by maintaining resiliency and focusing on solutions/liliRespectful by collaborating and actively listening/liliInsightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions/liliDirect by effectively communicating and conveying courage/li/ul/div

United States

Compétences linguistiques

English

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