Engineer II, AI/ML

Location: Hybrid role based in the United States: onsite 4 days per week in Richmond, Virginia, or onsite 2 days per week in Plano, Texas.

Salary: $88,800.00–$133,200.00 annually, with potential bonus and equity eligibility.

Company

hirify.global is a large used-car retailer focused on transparent vehicle sales and customer experiences, with more than 25,000 associates and over 250 locations.

What you will do

• Build and maintain production machine learning capabilities across feature engineering, training, evaluation, deployment, and model inference.
• Design agentic AI systems with tool use, orchestration, memory, evaluation harnesses, and production observability.
• Own monitoring and alerting for model performance, data drift, and prediction quality.
• Handle end-to-end on-call incident response and implement improvements that prevent recurring failures.
• Partner with Data Scientists, engineering teams, and product teams to turn experimental models into tested, maintainable, production-grade capabilities.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.
• At least 2 years of experience in software engineering, systems engineering, machine learning engineering, or AI engineering, including production application development and support.
• Proficiency in Python, Java, or C#, with hands-on experience using PyTorch or TensorFlow.
• Working knowledge of distributed databases, caching systems, and vector databases for high-throughput, low-latency workloads.
• Strong communication skills and experience working on a fast-paced, collaborative agile team in a product-oriented organization.
• Applicants must already be authorized to work full-time in the United States; visa sponsorship is not available for this role.

Nice to have

• Experience using AI coding agents with appropriate human verification.
• MLOps experience with experiment tracking, model registries, reproducible training, CI/CD, or automated retraining.
• Experience with model serving platforms and real-time inference, such as Azure ML, Databricks, or SageMaker.
• Experience designing or operating microservices and distributed architectures using containers, Kubernetes, or service-to-service APIs.

Culture & Benefits

• Collaborative, agile environment within a product-oriented organization.
• Commitment to training, career growth, diversity, and inclusion.
• Paid sick, vacation, and holiday time for eligible associates.
• Full-time salaried associates receive paid time away for sick leave, vacation, bereavement, jury duty, holidays, and related needs, subject to manager approval.