About this role
About Matroid
Matroid is a full-service computer vision company with an end-to-end platform that allows enterprise customers to rapidly train and deploy automated visual inspection on imagery, including EO, IR, X-Ray, CT, OCT, and others.
Founded in 2016 by a Stanford professor, Matroid serves a broad and rapidly growing customer base across manufacturing, automotive, logistics, aerospace, data center infrastructure, and security.
The Opportunity
Matroid is looking for a Vision Language Model (VLM) and Visual Foundation Model (VFM) Forward Deployed Engineer to operate at the forefront of visual and multimodal intelligence deployment in industry. You will build best-in-class AI systems that leverage vision-centric and vision-language models to solve challenging real-world use cases, including defect inspection, anomaly detection, assembly verification, process and safety monitoring, and multimodal understanding, retrieval, and reasoning over large collections of images, videos, and operational data.
You will work from the Palo Alto office, a five-minute walk from the Caltrain station and a nine-minute walk from Stanford University.
What You'll Do
- Train and deploy state-of-the-art vision-centric and vision-language models across industrial domains including manufacturing, automotive, logistics, aerospace, data center infrastructure, and security
- Deploy end-to-end CV systems across cloud, edge, and hybrid environments
- Define benchmarks and perform quantitative and qualitative evaluation of AI systems, including accuracy, reliability, latency, throughput, and robustness, then iterate to meet production requirements
- Design and develop industrial-grade imaging systems for high-quality, consistent data collection
- Integrate Matroid into customer workflows and systems, including manufacturing execution systems, PLCs, SCADA systems, quality management systems, safety alert systems, and video management systems
- Act as the technical expert, advising on all matters from technical scoping through model adaptation, deployment architecture, evaluation, integration, and customer enablement
- Design and lead product training sessions, technical workshops, and deployment playbooks that empower customers with AI
You Should Have
- Bachelor's degree in computer science, computer engineering, electrical engineering, machine learning, artificial intelligence, or another technical field
- Experience working with modern visual recognition models, including object detection, segmentation, tracking, action recognition, anomaly detection, and vision-language models for multimodal understanding, reasoning, and retrieval
- Strong Python coding skills, with the ability to build reliable systems that interact with models, APIs, databases, customer infrastructure, and production workflows
- Experience with popular machine learning and computer vision frameworks and tools such as PyTorch, TensorFlow, JAX, Hugging Face, NumPy, or OpenCV
- Strong ability to evaluate AI systems rigorously, including designing benchmarks, analyzing failure modes, and improving model performance through data, prompts, architecture, or workflow design
- Solid oral, written, presentation, and interpersonal communication skills, with the ability to address both technical and commercial audiences
Nice to Have
- Graduate degree with a concentration in computer vision, artificial intelligence, machine learning, natural language processing, robotics, or a related field
- Previous experience in forward-deployed engineering, field engineering, professional services, consulting, solutions engineering, or another customer-facing technical role
- Experience deploying AI systems in industrial, manufacturing, aerospace, logistics, security, or other operational environments
- Experience with complex computer vision and vision-language tasks such as spatiotemporal reasoning, open-world visual recognition, 3D visual understanding or reconstruction, or agentic workflows
- Experience at a high-growth technology startup