Senior Machine Learning Engineer

Collectors is the leading creator of innovative technology that provides value-added services for collectors worldwide. We grade, authenticate, vault, and sell millions of record-setting collectibles, all while modernizing and digitalizing the process to further our mission of helping collectors pursue their passions. We’re always on the lookout for talented people to join our growing team. Our services span collectible trading cards, autographs, comic books, coins, video games, event tickets, and memorabilia.

Our subsidiaries include PSA, PCGS, Beckett, SGC, and Card Ladder. Since our founding in 1986, we have graded and authenticated millions of items. We employ more than 3000 people across our headquarters in Santa Ana, California and offices in New Jersey, Texas, Florida, Japan, Shanghai, Hong Kong, Canada, Mexico, Germany, the UK, and France.

As part of our interview process, we request that candidates have their cameras on during video interviews. This helps foster meaningful conversation and allows us to create an experience that closely resembles our standard working environment. Certain interview steps may take place by phone. For remote roles, and at our discretion, candidates may be asked to participate in an on-site interview as part of the final stages of the process.

We understand there may be occasional circumstances requiring accommodation and are happy to discuss them as needed.

Collectors is the leading creator of innovative technology that provides value-added services for collectors worldwide. We grade, authenticate, vault, and help people research and manage the items they care about most. Our products bring authentication, grading, and trading into the modern era and make complex collector data more accessible.

Our engineering mission is to build trusted, scalable systems that improve the experience for every collector.

We’re looking for a Senior Machine Learning Engineer to join our AI/ML team and build applied machine learning systems from prototype through production. This role is ideal for an engineer who is equally comfortable training and evaluating models, designing production‑ready pipelines, and shipping tools that help internal teams make better decisions. You’ll work across computer vision, structured data, and agentic AI workflows, with direct impact on products used by graders, researchers, and collectors.

You’ll partner closely with product, engineering, operations, and domain experts to turn ambiguous problems into measurable, reliable ML solutions.

• Design, build, and deploy end-to-end machine learning systems that support AI/ML product initiatives
• Own projects from problem framing through implementation, evaluation, launch, and post‑launch monitoring, with clear accountability for outcomes
• Develop production‑grade computer vision, multimodal, and agentic pipeline solutions that can ingest images and other inputs, reason over uncertainty, and return structured, reliable outputs
• Build and improve data pipelines, model evaluation frameworks, and feedback loops that ensure training and inference systems remain accurate, scalable, and maintainable over time
• Partner with annotation, operations, product, and domain experts to define data requirements, labeling standards, success metrics, and rollout plans
• Translate experimental findings into clear technical recommendations, balancing model quality, latency, cost, and operational complexity
• Contribute high-quality code, documentation, and technical design artifacts, and collaborate effectively through design reviews, code reviews, and cross‑functional discussions

• 5+ years of experience in machine learning, applied AI, or a closely related software engineering field
• Strong hands‑on experience building and shipping machine learning systems in production, including data preparation, model training, evaluation, deployment, and monitoring
• Proficiency in Python and common ML tooling, along with solid software engineering fundamentals such as testing, modular design, observability, and version control
• Experience in one or more of the following areas: computer vision, multimodal modeling,…