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Forward Deployed Engineer

📅 May 18
PythonDockerKubernetesNetworking

📜 Description

  • 0-to-1 Deployment: Take validated proof-of-concepts from the pre-sales process and build the first production deployment. This includes data pipeline setup, model optimization, edge device configuration, and integration with customer infrastructure.
  • Embed with Customers: Work on-site or deeply embedded with the customer’s engineering team during the initial deployment phase (typically 4–12 weeks per engagement). Build trust, transfer knowledge, and establish the foundation for long-term success.
  • Knowledge Transfer & Handoff: Document your deployment architecture, create runbooks, and train the customer’s team so they can operate the system independently. Provide a clean handoff to Roboflow’s Implementation Engineers for scaling and expansion.
  • De-risk New Deployments: Identify and resolve technical risks early. If a customer’s environment won’t support the planned architecture, you find the alternative before it becomes a project failure.
  • Shape the Deployment Playbook: Codify repeatable deployment patterns, starter templates, and reusable artifacts that make future deployments faster and more reliable.

🛠️ Requirements

  • et You'll Bring
  • Meaningful experience deploying technology in physical-world environments. We value breadth, working across different industries, hardware platforms, and deployment contexts, over depth at a single company. The best
  • Strong proficiency in Python; experience with systems-level work (Docker, Kubernetes, networking, Linux) is highly valued.
  • Hands-on experience deploying machine learning or computer vision models to production; you understand the gap between a working notebook and a reliable pipeline.
  • Experience with edge computing hardware and constraints (NVIDIA Jetson, industrial cameras, limited connectivity, on-premise security requirements).
  • Excellent troubleshooting and debugging skills; you're the person who figures out why it works in staging but not in production.

Benefits

  • $4000/yr Travel Stipend to travel anywhere anytime to work alongside other Roboflowers
  • $150/mo Team lunch
  • $500/one time Home office
  • Cover up to 100% of your health insurance costs for you and your partner or family
  • Edge-First Engineering: Deploy and operate computer vision systems on edge hardware in physical environments. Where conditions are unpredictable and connectivity is unreliable. This is hands-on, hardware-heavy work.
  • Production Engineering: Write production-grade code that will live in the customer’s environment. Handle the messy realities of real-world computer vision: lighting variability, camera calibration, model drift, network latency, and edge hardware constraints.
Reddit

Software Engineer - Data Movement Platform

Reddit👥 1001 - 5000 employees🏢 Online Community/social Media
🔥 6 hours ago

As a Software Engineer on the Data Movement team, you will enhance scalable data infrastructure and streamline data processing for machine learning and analytics at Reddit.

Software EngineeringData InfrastructureMachine LearningAnalytics

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