Senior Machine Learning Engineer (AI)

Location: US - Remote

Company

hirify.global provides technology and services for grading, authenticating, vaulting, researching, and selling collectibles, including trading cards, autographs, comics, coins, video games, tickets, and memorabilia.

What you will do

• Design, build, deploy, and monitor end-to-end machine learning systems for AI/ML products.
• Own projects from problem framing through implementation, evaluation, launch, and post-launch monitoring.
• Develop production-grade computer vision, multimodal, and agentic AI pipelines that process images and other inputs and return reliable structured outputs.
• Build data pipelines, model evaluation frameworks, and feedback loops for accurate, scalable, and maintainable training and inference systems.
• Partner with annotation, operations, product, engineering, and domain experts to define data requirements, labeling standards, metrics, and rollout plans.
• Translate experiments into technical recommendations while balancing model quality, latency, cost, and operational complexity.

Requirements

• 5+ years of experience in machine learning, applied AI, or a closely related software engineering field.
• Hands-on experience shipping production machine learning systems, including data preparation, training, evaluation, deployment, and monitoring.
• Proficiency in Python and common ML tooling, with strong software engineering fundamentals in testing, modular design, observability, and version control.
• Experience with computer vision, multimodal modeling, information extraction, search and retrieval, or LLM-based systems.
• Ability to define statistically sound evaluation methodologies and make data-driven model readiness and trade-off decisions.
• Ability to work legally in the United States; employment eligibility is validated through e-Verify.

Nice to have

• Experience with image-heavy or quality-sensitive domains such as inspection, authentication, fraud detection, or document and image understanding.
• Experience with agentic systems, tool-using LLMs, verification loops, retrieval, and structured outputs.
• Familiarity with cloud ML infrastructure, experiment tracking, and production inference patterns.
• Experience collaborating with human-in-the-loop operations, annotation teams, or domain specialists.
• Interest in collectibles, trading cards, marketplaces, or trust-and-safety problems.

Culture & Benefits

• Work with product, engineering, operations, and domain experts on systems used by graders, researchers, and hirify.global.
• Contribute through technical design, code reviews, design reviews, documentation, and cross-functional discussions.
• Remote roles may include an on-site interview during the final hiring stages.
• Video interviews require cameras to be on, with accommodations available when needed.

Hiring process

• Interview stages may take place by video or phone.
• Remote candidates may be asked to participate in an on-site final-stage interview.