Senior Machine Learning Engineer

3 days ago


Remote, Oregon, United States Credit Acceptance Full time
About the Role

Credit Acceptance is a leading provider of used car financing solutions, and we're seeking a highly skilled Senior Machine Learning Engineer to join our team. As a key member of our AI/ML Platform team, you will be responsible for designing, building, and maintaining end-to-end ML/AI platforms to support and automate the lifecycle of machine learning and Gen AI workflows.

Key Responsibilities
  • Develop, maintain, and enhance reusable frameworks for AI/ML model development and deployment.
  • Partner with the Cloud Engineering team to execute strategic plans, including road mapping and technical designs for feature, training, serving infrastructure, and underlying operational infrastructure.
  • Design, advocate, and implement cutting-edge technologies for availability, scalability, operational excellence, and cost management.
  • Collaborate closely with ML and Tech Delivery Engineers, Business Ops, and Product Managers to understand their needs and identify opportunities to improve the efficiency of the AI/ML process.
  • Stay up-to-date with industry and academic developments in the SOTA for the AI lifecycle and ML Systems domain, and adopt technology that best fits business and industry needs.
  • Partner, mentor, and educate ML and Data Engineers on current and up-and-coming tools and technologies for ML operations.
  • Help design and architect an AI platform that adheres to the principles of responsible AI and simplifies privacy compliance.
  • Utilize expertise in 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 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.
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.
What We Offer
  • A competitive base salary + an annual variable bonus (cash and equity) will range from $243,000 to $417,000.
  • The position will also be eligible for a sign-on RSU grant.
  • Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/dental/vision, and many non-standard benefits that make us a Great Place to Work.


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