Senior VLM & VFM Field Engineer

About Matroid

Matroid helps enterprises build and operate computer vision systems through an end-to-end platform for training, evaluating, and deploying automated visual inspection. The platform supports a wide range of imagery, including EO, IR, X-Ray, CT, and OCT.

Founded in 2016 by a Stanford professor, Matroid works with customers across aerospace, automotive, manufacturing, logistics, data center infrastructure, and security, including Mercedes-Benz, Toyota, Boeing, Google, Amazon, and Bosch.

The Opportunity

Matroid is hiring a Senior Vision-Language Model (VLM) and Visual Foundation Model (VFM) Field Engineer to build and deploy production-grade deep learning systems using Matroid's platform for a broad range of enterprise customers.

You will work directly with customers to understand their operations and turn challenging requirements into reliable computer vision and multimodal AI solutions. As the technical owner of complex engagements, you will guide architecture, model adaptation, evaluation, integration, and deployment, combining Matroid's platform with custom engineering.

Projects will cover defect inspection, anomaly detection, assembly verification, process and safety monitoring, and multimodal understanding, retrieval, and reasoning across images, videos, and operational data. Alongside delivery, you will use lessons from customer deployments to improve the platform and engineering practices.

What You'll Do

- Build and deploy deep learning systems on Matroid using visual foundation models, vision-language models, and specialized vision-centric models for object detection, segmentation, tracking, anomaly detection, spatiotemporal reasoning, and multimodal understanding and retrieval

- Own technical delivery from scoping and feasibility assessment through model selection, fine-tuning, prompt engineering, system architecture, and production deployment

- Develop deep learning systems that operate in cloud, edge, and hybrid environments, optimizing inference latency, GPU utilization, memory consumption, and throughput while balancing accuracy, cost, and maintainability

- Establish representative evaluation datasets and task-specific benchmarks; analyze failure modes and improve model accuracy and robustness through data curation, targeted augmentation, and system adaptation

- Develop imaging and data collection systems, selecting cameras, optics, illumination, and capture configurations that support reliable visual recognition in demanding environments

- Connect Matroid to customer equipment and software, including PLCs, manufacturing execution systems, SCADA, quality management platforms, safety alerting, and video management systems

- Guide customers through technical decisions and troubleshoot complex issues across model behavior, inference pipelines, infrastructure, and integrations

- Review architecture and code, and build reusable tools for model evaluation, inference, and deployment

- Work with product and engineering colleagues to translate deployment insights into improvements in model capabilities, performance, and platform workflows

- Deliver technical workshops, training, and documentation that help customers evaluate, adopt, and operate their AI systems successfully

You Should Have

- Master's degree or higher in computer science, computer engineering, electrical engineering, machine learning, artificial intelligence, robotics, or a closely related technical discipline

- Strong experience with visual recognition tasks such as detection, segmentation, tracking, action recognition, and anomaly detection, plus hands-on work adapting and evaluating visual foundation models or vision-language models

- Excellent Python skills and sound software engineering practices for building systems that connect models, APIs, databases, and customer infrastructure

- Proficiency with relevant tools and frameworks such as PyTorch, TensorFlow, JAX, Hugging Face, NumPy, and OpenCV

- Experience developing rigorous evaluations and improving AI performance through better data, model adaptation, prompts, architecture, or workflow design

- Demonstrated ability to make architecture decisions and resolve reliability, performance, and integration problems in deployed systems

- Experience leading complex technical projects and collaborating across teams

- Clear written, verbal, and presentation skills in English, including the ability to explain technical decisions and tradeoffs to both technical and business audiences

Nice to Have

- 3+ years of industry experience focused on computer vision, AI, robotics, machine learning, natural language processing, or a related discipline

- Experience in spatiotemporal reasoning, open-world recognition, 3D understanding or reconstruction, or agentic workflows

- Background in forward-deployed engineering, field engineering, solutions engineering, or another customer-facing technical position

- Experience deploying AI in aerospace, automotive, manufacturing, logistics, security, or similarly demanding operational settings

- Experience at a growing technology startup