Vision AI Solutions Engineer

Ultralytics; Austin (TX); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Competitive compensation

On-site collaboration (Austin)

Flexible working hours

Generous vacation days

MacBook Air/Pro, Studio Display & AirP

Learning & development budget

Job summary

Ultralytics is seeking a Solutions Engineer in Austin to turn complex computer vision problems into production systems built on YOLO. You will lead technical discovery, design architectures, build benchmarks and POCs, and guide customers from initial conversations to deployed models.

You will collaborate with Sales, Customer Success, Product, and Engineering while engaging with customers across manufacturing, retail, security, and robotics.

Qualifications

• Strong Python and practical experience with YOLO, OpenCV, PyTorch, and computer vision.
• Experience training, optimizing, evaluating, and deploying ML models.
• Comfortable with Docker, Git, REST APIs, Linux, cloud platforms, and edge workflows.
• Experience deploying across Linux, macOS, and Windows environments.
• Proven ability to deliver technical demos, workshops, architecture reviews, and POCs.

Responsibilities

• Own technical discovery, translate customer needs into architectures, and define measurable success criteria.
• Evaluate customer data, recommend models, and design training, inference, and deployment strategies.
• Lead technical qualification and solution design alongside Account Executives and Customer Success Managers.
• Build Python prototypes with YOLO, OpenCV, PyTorch, and Docker.
• Create benchmarks, integrations, and production‑ready training and deployment workflows.
• Deploy solutions across Linux, macOS, Windows, cloud, and edge environments.
• Diagnose performance, data quality, inference, and hardware acceleration challenges.
• Use the Ultralytics documentation and YOLO guides to deliver reliable customer outcomes.
• Deliver technical demos, workshops, architecture reviews, and POCs that move opportunities forward.
• Explain ML concepts to engineers, operators, executives, and non‑technical audiences.
• Build trusted relationships and manage technical stakeholders from evaluation through production.
• Turn customer solutions into reusable examples, deployment guides, integrations, and documentation.
• Share feedback with Product and Engineering to improve the YOLO ecosystem.
• Engage developers through the Ultralytics community and GitHub.

Skills

Python

YOLO

OpenCV

PyTorch

Docker

Git

REST APIs

Linux

Cloud platforms

Edge workflows

Tools

YOLO

OpenCV

PyTorch

Docker

Git

REST APIs

Job description

Ultralytics is seeking a Solutions Engineer in Austin to turn complex computer vision problems into production systems built on YOLO. You will lead technical discovery, design architectures, build benchmarks and POCs, and guide customers from initial conversations to deployed models.

You will collaborate with Sales, Customer Success, Product, and Engineering while engaging with customers across manufacturing, retail, security, and robotics.