Forward Deployed Engineer - Singapore

About the role

Roboflow, which builds tools and resources for computer vision AI, is hiring Forward Deployed Engineers (FDEs) in Singapore. FDEs are the first technical hands on new customer deployments: after sales and solutions architecture validate the technical approach, you take a proof-of-concept from 0 to 1, embedding with the customer's engineering and operations teams to build and deploy their first production computer vision workflows. Once the deployment works and the customer's team can operate it, you hand off to Implementation Engineers.

Key responsibilities

• Take validated proof-of-concepts and build the first production deployment, including data pipelines, model optimization, edge device configuration and integration with customer infrastructure.
• Deploy and operate computer vision systems on edge hardware in physical environments with unpredictable conditions and unreliable connectivity.
• Work on-site or deeply embedded with the customer's engineering team for 4-12 weeks per engagement, building trust and transferring knowledge.
• Write production-grade code and handle real-world issues such as lighting variability, camera calibration, model drift, network latency and edge hardware constraints.
• Document the deployment architecture, create runbooks and train the customer's team, then hand off to Implementation Engineers.
• Identify and resolve technical risks early, and codify repeatable deployment patterns, starter templates and reusable artifacts.

Required profile

• Experience deploying technology in physical-world environments, across different industries, hardware platforms and contexts.
• Hands-on experience deploying machine learning or computer vision models to production.
• Experience with edge computing hardware and constraints (NVIDIA Jetson, industrial cameras, limited connectivity, on-premise security).
• Strong troubleshooting skills and strong interpersonal skills, able to talk to executives, engineers and machine operators.
• Willingness to travel about 40-50% for on-site customer deployments.
• Preferred: experience in professional services, deployment engineering or forward deployed engineering; familiarity with CV/MLOps tooling; background in IoT, embedded systems or infrastructure engineering; deep industrial subject matter expertise.

Required skills

• Python
• Docker, Kubernetes, networking, Linux (highly valued)
• Edge computing hardware and computer vision model deployment

What we offer

• $4,000 USD per year travel stipend and a $3,500 USD home office gift.
• $350 per month productivity stipend and $350 per month AI tools allowance.
• $150 per month team lunch.
• Equity in the company.
• A distributed team with occasional in-person get-togethers and a $4,000 USD per year travel stipend.