Roboflow

2 months ago

Forward Deployed Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Embedded with customer engineering teams to deploy production computer vision workflows from proof-of-concept to production. You’ll build data pipelines, configure edge devices, and ship production-grade code while surfacing field feedback to Product and Engineering to shape Roboflow’s platform. Expect high autonomy, field work, and travel as you deploy in diverse environments.

Location: New York, San Francisco

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•0-to-1 Deployment: Take validated proof-of-concepts from the pre-sales process and build the first production deployment, including data pipeline setup, model optimization, edge device configuration, and integration with customer infrastructure.
•Edge-First Engineering: Deploy and operate computer vision systems on edge hardware in physical environments with intermittent connectivity.
•Embed with Customers: Work on-site or deeply embedded with the customer’s engineering team during the initial deployment phase (4–12 weeks per engagement).
•Production Engineering: Write production-grade code in the customer’s environment, addressing real-world CV challenges like lighting, calibration, drift, latency, and hardware constraints.
•Be Our Eyes and Ears in the Field: Surface gaps between customer needs and actual requirements to inform Product/Engineering priorities.

Travel: High travel

Pay and Benefits

Equity and Bonus:Equity

Perks:Travel AllowanceHealth InsuranceEquityHome OfficeAi ToolsProductivity Stipend

Key Requirements

•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)
•Willingness to travel ~40–50% for on-site customer deployments
•Excellent troubleshooting and debugging skills; strong interpersonal skills to collaborate with executives, engineers, and machine operators

Experience:ManufacturingLogisticsRetail

Skills:PythonDockerKubernetesLinuxEdge computingNVIDIA JetsonComputer visionProduction deploymentOn-premise security

Tech Stack:PythonDockerKubernetesLinuxNVIDIA JetsonEdge computingComputer vision

Company Brief

Roboflow

Provides a computer vision platform that helps teams build, deploy, and manage object detection and image classification models. Offers tooling for dataset versioning, annotation, augmentation, and production-ready model hosting and monitoring.

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Headquarters: Boston, United States

Founded: 2016

Website LinkedIn

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Roboflow

2 months ago

Forward Deployed Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: New York, San Francisco

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•0-to-1 Deployment: Take validated proof-of-concepts from the pre-sales process and build the first production deployment, including data pipeline setup, model optimization, edge device configuration, and integration with customer infrastructure.
•Edge-First Engineering: Deploy and operate computer vision systems on edge hardware in physical environments with intermittent connectivity.
•Embed with Customers: Work on-site or deeply embedded with the customer’s engineering team during the initial deployment phase (4–12 weeks per engagement).
•Production Engineering: Write production-grade code in the customer’s environment, addressing real-world CV challenges like lighting, calibration, drift, latency, and hardware constraints.
•Be Our Eyes and Ears in the Field: Surface gaps between customer needs and actual requirements to inform Product/Engineering priorities.

Travel: High travel

Pay and Benefits

Equity and Bonus:Equity

Perks:Travel AllowanceHealth InsuranceEquityHome OfficeAi ToolsProductivity Stipend

Key Requirements

•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)
•Willingness to travel ~40–50% for on-site customer deployments
•Excellent troubleshooting and debugging skills; strong interpersonal skills to collaborate with executives, engineers, and machine operators

Experience:ManufacturingLogisticsRetail

Skills:PythonDockerKubernetesLinuxEdge computingNVIDIA JetsonComputer visionProduction deploymentOn-premise security

Tech Stack:PythonDockerKubernetesLinuxNVIDIA JetsonEdge computingComputer vision

Company Brief

Roboflow

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Scaleup

Headquarters: Boston, United States

Founded: 2016

Website LinkedIn