Work on Computer Vision implementation project for an international healthcare company.
Collaborate with cross-functional teams to ensure successful project delivery.
Manage project timelines, budgets, and resources.
Communicate progress and challenges to stakeholders and management.

Requirements

Any experience with Roboflow or similar platforms like SuperAnnotate, V7 Darwin, Nyckel, VisionRepo, Kili Technology, Chooch AI, and Datature, among others, for computer vision model training, annotation, and deployment.
Understanding of computer vision and ML pipelines (data → labeling → training → deployment → evaluation).
Ability to interpret model metrics (mAP, precision, recall, confusion patterns) and relate them to operational KPIs.
Comfort discussing inference performance, edge deployment constraints, latency/throughput considerations.
Familiarity with cloud environments, APIs, and common integration patterns.
Ability to troubleshoot at a conceptual level to identify where to engage Support, NTSE, Implementation, or Engineering.
Background in ML Ops, applied ML, industrial automation, or complex SaaS deployments.
Experience managing global rollouts or multi-site production deployments.
Familiarity with Jetson devices, industrial cameras, or real-time inference systems.
Experience quantifying business value from ML or automation solutions.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

computer visionML pipelinesmodel metricsmAPprecisionrecallcloud environmentsML Opsindustrial automationSaaS deployments

Soft Skills

collaborationproject managementcommunicationtroubleshootingstakeholder engagement