{"id":924949,"url":"https://alion.io/job/matroid-senior-vlm-vfm-field-engineer","title":"Senior VLM & VFM Field Engineer","company":{"id":37106,"name":"Matroid","domain":"matroid.com","url":"https://alion.io/company/matroid","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":{"grade":"C","score":65,"open_postings":12,"ghost_share":0.583,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Solutions","role_family":"Solutions","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":145000,"max_usd":290000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1026},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Computer Vision","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Hugging Face","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NumPy","optional":false},{"name":"OpenCV","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"VLM","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"AI Agents","optional":true}],"status":"live","first_seen_at":"2026-09-15T01:47:49Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-11-06T02:37:46Z","board_verified":true,"closed_at":null,"days_open":52,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":52},"description":"Senior Vision-Language Model (VLM) & Visual Foundation Model (VFM) Field Engineer\nAbout Matroid\nMatroid 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.\nFounded in 2016 by a Stanford professor, Matroid works with customers across aerospace, automotive, manufacturing, logistics, data center infrastructure, and security.\nWe’re hiring a Senior Vision-Language Model (VLM) & 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, such as Mercedes-Benz, Toyota, Boeing, Google, Amazon, Bosch, and many others.\nYou’ll 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’ll guide architecture, model adaptation, evaluation, integration, and deployment, combining Matroid’s platform with custom engineering.\nProjects 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’ll use lessons from customer deployments to improve our platform and engineering practices.\nThis role is based at our downtown Palo Alto office, a five-minute walk from Caltrain and a nine-minute walk from Stanford University.\nWhat you’ll be doing\nBuild and deploy deep learning systems on Matroid using visual foundation models, vision-language models, and/or specialized vision-centric models for object detection, segmentation, tracking, anomaly detection, spatiotemporal reasoning, and multimodal understanding and retrieval.\nOwn technical delivery from scoping and feasibility assessment through model selection, fine-tuning, prompt engineering, system architecture, and production deployment.\nDevelop deep learning systems that can operate in cloud, edge, and hybrid environments, optimizing inference latency, GPU utilization, memory consumption, and throughput while balancing accuracy, cost, and maintainability.\nEstablish representative evaluation datasets and task-specific benchmarks. Analyze failure modes and improve model accuracy and robustness through data curation, targeted augmentation, and DL system adaptation.\nDevelop imaging and data collection systems, selecting cameras, optics, illumination, and capture configurations that support reliable visual recognition in demanding environments.\nConnect Matroid to customer equipment and software, including PLCs, manufacturing execution systems, SCADA, quality management platforms, safety alerting, and video management systems.\nGuide customers through technical decisions and troubleshoot complex issues across model behavior, inference pipelines, infrastructure, and integrations.\nReview architecture and code, and build reusable tools for model evaluation, inference, and deployment.\nWork with product and engineering colleagues to translate deployment insights into improvements in model capabilities, performance, and platform workflows.\nDeliver technical workshops, training, and documentation that help customers evaluate, adopt, and operate their AI systems successfully.\nHow you’ll be doing it\nTake ownership. Bring structure to ambiguous requirements, identify risks early, and drive projects through production readiness.\nStay hands-on. Write code, adapt models, investigate data, and debug systems while providing technical direction.\nChoose models thoughtfully. Assess capabilities and limitations, and select the right combination of fine-tuning, prompting, specialized models, and orchestration for each application.\nBuild deep platform expertise. Understand Matroid’s capabilities and apply its features, workflows, and integrations effectively.\nUnderstand customer operations. Account for production constraints and communicate clearly with engineers, operators, and business stakeholders.\nRaise the team’s technical standard. Share deployment lessons, offer practical feedback, and help other engineers develop their judgment.\nWork independently and collaboratively. Make progress with autonomy and bring in teammates when their expertise will improve the outcome.\nKeep learning. Evaluate advances in computer vision and multimodal AI and turn promising approaches into practical customer capabilities.\nWhat you bring to the table\nA master’s degree or higher in computer science, computer engineering, electrical engineering, machine learning, artificial intelligence, robotics, or a closely related technical discipline.\nStrong 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.\nExcellent Python skills and sound software engineering practices for building systems that connect models, APIs, databases, and customer infrastructure.\nProficiency with relevant tools and frameworks, such as PyTorch, TensorFlow, JAX, Hugging Face, NumPy, and OpenCV.\nExperience developing rigorous evaluations and improving AI performance through better data, model adaptation, prompts, architecture, or workflow design.\nDemonstrated ability to make architecture decisions and resolve reliability, performance, and integration problems in deployed systems.\nExperience leading complex technical projects and collaborating across teams.\nClear written, verbal, and presentation skills in English, including the ability to explain technical decisions and tradeoffs to both technical and business audiences.\nBonus points if...\n You have 3+ years of industry experience focused on computer vision, AI, robotics, machine learning, natural language processing, or a related discipline.\nYou have experience in spatiotemporal reasoning, open-world recognition, 3D understanding or reconstruction, or agentic workflows.\nYou have worked in forward-deployed engineering, field engineering, solutions engineering, or another customer-facing technical position.\nYou have deployed AI in aerospace, automotive, manufacturing, logistics, security, or similarly demanding operational settings.\nYou have experience at a growing technology startup.\nWhat we offer in return\nCompetitive compensation and equity.\nChallenging technical work with direct customer impact.\nReimbursement for gym memberships.\nDaily lunch, drinks, and snacks.\nFully paid premiums for medical, dental, and vision coverage.\nScheduling flexibility to accommodate interests outside work.\nA budget for the hardware and software you need to succeed.\nLearning resources covering software engineering, computer vision, VLMs, LLMs, and multimodal AI.\nA downtown Palo Alto office close to Caltrain.\nMatroid is an equal-opportunity employer committed to a diverse workplace. 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