9 hours ago
Singapore, SingaporeSenior
Responsibilities
- Take validated proof-of-concepts from the pre-sales process through first production deployment.
- Set up data pipelines, optimize models, configure edge devices, and integrate systems with customer infrastructure.
- Deploy and operate computer vision systems on edge hardware in physical environments with unreliable connectivity.
- Write production-grade code and address lighting variability, camera calibration, model drift, network latency, and hardware constraints.
- Embed with customer engineering and operations teams, build trust, transfer knowledge, and establish deployment foundations.
- Document deployment architecture, create runbooks, train customer teams, and hand off deployments to Implementation Engineers.
- Identify technical risks, develop alternative architectures when needed, and de-risk new deployments.
- Create repeatable deployment patterns, starter templates, and reusable deployment artifacts.
- Surface customer needs and field insights to Roboflow Product and Engineering teams.
Requirements
- Meaningful experience deploying technology in physical-world environments such as factories, warehouses, construction sites, or labs.
- Strong proficiency in Python.
- Experience deploying machine learning or computer vision models to production.
- Experience with edge computing hardware and constraints, including NVIDIA Jetson, industrial cameras, limited connectivity, and on-premise security requirements.
- Systems-level experience with Docker, Kubernetes, networking, and Linux is highly valued.
- Strong troubleshooting and debugging skills in production environments.
- Strong interpersonal skills for working with executives, engineers, and machine operators.
- Experience in one or more target verticals: manufacturing, logistics, food processing, automotive, or retail.
- Willingness to travel approximately 40–50% for on-site customer deployments.
- Preferred experience in professional services, deployment engineering, or forward deployed engineering.
- Familiarity with computer vision and MLOps tooling and practices, including model versioning, monitoring, and retraining pipelines.
- Preferred industrial subject matter expertise or background in IoT, embedded systems, or infrastructure engineering.
Benefits
- Singapore-based distributed work arrangement with the option to work from home, a co-working space, or another preferred location.
- Approximately 40–50% travel for customer deployments and a $4000 USD/yr travel stipend for company travel.
- $350/mo productivity stipend, $350/mo AI tools stipend, $150/mo team lunch stipend, and a $500 one-time home office stipend.
- Equity in the company.
- Asynchronous work with a small number of synchronous meetings outside standard Singapore hours and regular team onsites.
- Equal opportunity workplace with a globally distributed team.
Tech Stack
Categories
Forward Deployed
About Roboflow
Roboflow provides SaaS developer tools for computer vision, covering dataset management, annotation, preprocessing, model training, and deployment via API or to edge devices. The platform is used by over 1 million developers and teams in industries like manufacturing, logistics, retail, and research. The privately held, remote-first company raised a Series B in 2024.