Principal Engineer, ML/AI Platform at Credit Acceptance Corporation
Atlanta, GA
About the Job
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!
The ML/AI Platform team at Credit Acceptance (CA) designs builds and maintains end-to-end ML/AI platforms to support and automate the lifecycle of the machine learning and Gen AI workflows, including standardization of dev environment, auto-labeling, feature stores and experiment management, model development, debugging and evaluation, containerization, deployment, and monitoring. The team also manages all the internal and external tools integrated into the platform for seamless ML/AI operations. Besides managing the central ML and Gen AI platform, the team is also responsible for designing and building custom large-scale and efficient end-to-end solutions that can be seamlessly integrated with other systems and processes.
As a leader within the team, you will help democratize ML/AI and its applications for Credit Acceptance, ensuring it remains easily accessible, robust, trustable, scalable, and cost-efficient. You will meet our internal customers where they are and optimize towards their needs by delivering value incrementally and coupled to their problems. Being part of a small yet impactful team means having a broad scope of responsibility, and as ML is still in its early stages, this role provides a chance to grow as a leader by mentoring others across the company. This is an exciting opportunity to own and help define the future of machine learning within a rapidly growing team!
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
- Develop, maintain, and enhance reusable frameworks for AI/ML model development and deployment while establishing and driving best practices in machine learning engineering and Operations.
- Partner with the Cloud Engineering team in the strategic execution, including the road mapping and the technical designs for the feature, training, serving infrastructure, and underlying operational infrastructure that provides incremental delivery and impact.
- Design, advocate, and implement cutting edge technologies for availability, scalability, operational excellence, and cost management while delivering incrementally.
- Collaborate closely with the ML and Tech Delivery Engineers, and Business Ops and Product Managers to understand their needs and identify opportunities to improve the efficiency of the AI/ML process.
- Closely follow industry and academic developments in the SOTA for the AI lifecycle and ML Systems domain’s and adopt technology that is the best fit for business and industry needs
- Partner, mentor and/or educate ML and Data Engineers on current and up and coming tools and technologies for ML operations through presentations and documentation.
- Help design and architect an AI platform that adheres to the principles of responsible AI and simplifies privacy compliance.
- Utilize your deep understanding of data characteristics, model architectures, optimization techniques, or other ML domain-specific challenges to perform critical analysis of modeling results
- Lead build vs buy discussions on technologies that would underpin the feature, training, and serving layers.
- Conduct technical interviews with well-calibrated standards and play an essential role in recruiting activities.
- Effectively onboard and mentor junior engineers and/or interns
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
- Bachelor’s Degree in Computer Science, Math, or equivalent real-world experience
- Bachelor’s Degree with 8+ years or Master’s Degree with 6+ years or PhD with 4+ years of working high-scale distributed or ML platforms or systems for training, deploying complex ML models by employing SOTA techniques in the area of distributed training and deployment for real-time and batch processing, and managing dev-ops tools such as Kubernetes
- Expertise in using Python, Java or C++ and deploying on cloud platforms such as AWS, Azure, or GCP
- Strong expertise in writing production-quality code and setting standards for code quality across engineering teams
- Experience in driving technical strategy and vision for engineering teams and organizations
- Leadership experience in planning and execution of cross-functional initiatives and projects with a track record of efficiently solving complex problems collaboratively on larger teams
- In-depth understanding of SDLC and best practices - CI/CD, coding, debugging, optimization, testing, integration and deployment
- Experience working on scaling challenges associated with building LLMs and/or other large foundational models.
- A problem solver with attention to detail, a passion for truth, and openness to dealing with unknown while wearing many hats
Target Compensation: A competitive base salary + an annual variable bonus (cash and equity) will range from $202,500 to $417,000. The position will also be eligible for a sign-on RSU grant.
Final compensation within the range is influenced by many factors including role-specific skills, depth and experience level, industry background, relevant education and certifications, and geographic location.
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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.
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.