Job Overview
Location
NY, SF or Remote (US)
Job Type
Full-time
Category
Software Engineering
Date Posted
May 21, 2026
Full Job Description
đź“‹ Description
- • Deploy and operationalize the first production-grade computer vision workflows for new enterprise customers, transitioning validated proof-of-concepts from pre-sales into live, real-world systems.
- • Embed directly with customer engineering and operations teams for 4–12 weeks per engagement, working on-site or remotely to build, configure, and debug computer vision systems in unpredictable physical environments.
- • Configure and deploy computer vision models on edge hardware such as NVIDIA Jetson, industrial cameras, and other constrained devices where connectivity is unreliable and environmental conditions vary.
- • Build and optimize data pipelines that ingest video feeds, handle camera calibration, manage model drift, and adapt to real-world variables like lighting changes, occlusions, and network latency.
- • Write production-grade Python code that integrates Roboflow’s platform with customer infrastructure, including on-premise systems, security protocols, and legacy software environments.
- • Diagnose and resolve technical failures that occur only in production—where systems work in staging but fail under real operational load, network restrictions, or hardware limitations.
- • Serve as the primary technical liaison between customers and Roboflow’s Product and Engineering teams, collecting and synthesizing feedback on usability gaps, unmet needs, and unanticipated use cases.
- • Document deployment architectures, create detailed runbooks, and train customer teams to independently operate, monitor, and maintain the deployed computer vision systems.
- • Identify technical risks early in the deployment lifecycle and proactively redesign solutions when customer environments deviate from expected architectures.
- • Codify repeatable deployment patterns, starter templates, and reusable components to accelerate future deployments and improve scalability across the customer base.
- • Work across diverse verticals including manufacturing, logistics, food processing, automotive, and retail, adapting deployment strategies to industry-specific workflows and safety requirements.
- • Travel 40–50% of the time to customer sites for on-site deployments, often working in non-office environments such as factories, warehouses, construction sites, and laboratories.
- • Collaborate with Sales, Solutions Architecture, and Implementation Engineering teams to ensure seamless handoffs from pre-sales validation to production scale.
- • Maintain a hands-on, builder mindset: prioritize shipping working systems over theoretical discussions, and solve problems that require physical interaction with hardware, networks, and real-world systems.
🎯 Requirements
- • Meaningful experience deploying technology in physical-world environments such as factories, warehouses, or labs
- • Strong proficiency in Python and hands-on experience with Docker, Kubernetes, Linux, and networking
- • Proven ability to deploy machine learning or computer vision models to production edge hardware under real-world constraints
- • Willingness to travel 40–50% for on-site customer deployments
- • Excellent troubleshooting skills with a track record of diagnosing production-only failures
- • Strong interpersonal skills to build trust with customer engineers, executives, and frontline operators
🏖️ Benefits
- • $4000/yr Travel Stipend to work alongside other Roboflowers anywhere in the world
- • $350/mo Productivity stipend for home office, internet, or co-working space expenses
- • $350/mo AI Tools stipend
- • $150/mo Team lunch stipend
- • $500 one-time home office setup allowance
- • Coverage of up to 100% of health insurance costs for employee, partner, and family
- • Equity in the company
- • Flexible work schedule with asynchronous and synchronous collaboration options
- • Opportunities to work from NYC, SF, or remotely across the US
Skills & Technologies
Python
Docker
Kubernetes
GitHub
Linux
Remote
About Roboflow, Inc.
Roboflow provides a cloud-based platform for computer vision teams to manage datasets, annotate images and video, train custom models, and deploy them to edge devices and production APIs. The service automates data preprocessing, augmentation, version control, and performance monitoring across YOLO, TensorFlow, PyTorch, and other frameworks, enabling developers and enterprises to accelerate vision projects from prototype to scalable applications without building infrastructure from scratch.
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