Solutions Engineer

Ultralytics

Solutions Engineer turning complex vision problems into YOLO production systems. Collaborating with clients across various sectors to deliver impactful AI solutions.

Posted 7/30/2026full-timeAustin • Texas • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python programming and machine learning model deployment, with a strong focus on computer vision technologies such as YOLO and OpenCV. Capable of leading technical discovery and delivering impactful solutions across diverse environments while effectively communicating with both technical and executive stakeholders.

Highest-signal resume keywords

Python ProgrammingYOLO ExpertiseMachine Learning DeploymentTechnical CommunicationDocker Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

YOLOOpenCVPyTorchMachine LearningDockerLinuxCloud PlatformsCI/CDMLOpsREST APIs

Soft Skills

Strong CommunicationIndependent OwnershipResilienceCustomer FocusRelationship Management

Tools & Technologies

GitKubernetesCUDATensorRTONNXJetsonAWSAzureGCPUltralytics Documentation

Industry Keywords

Computer VisionTechnical DemosArchitecture ReviewsProof-of-ConceptsOpen Source Contributions

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesLinuxMacOSOpen SourcePythonPyTorch

About the role

Key responsibilities & impact

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 proof-of-concepts that move opportunities forward.
Explain machine learning clearly to engineers, operators, executives, and other 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 organization.

Requirements

What you’ll need

Strong Python and practical experience with YOLO, OpenCV, PyTorch, and computer vision.
Experience training, optimizing, evaluating, and deploying machine learning 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.
Strong communication skills with both technical and executive audiences.
Independent ownership, urgency, resilience, and results in a high-performance startup environment.
Passion for AI, open source, and helping customers achieve real outcomes.
Nice to have: Kubernetes, CUDA, TensorRT, ONNX, Jetson, or other edge accelerators.
Experience with MLOps, model monitoring, CI/CD, or observability.
Familiarity with AWS, Azure, GCP, serverless systems, or managed inference platforms.
Experience integrating OpenAI or Anthropic APIs into customer tools.
Open-source contributions or experience supporting developer communities.
Knowledge of Ultralytics YOLO workflows and production computer vision solutions.

Benefits

Comp & perks

Competitive compensation: Competitive compensation packages
On-site collaboration: Work with passionate builders in one of our global hubs (NYC/Austin).
Flexible working hours: We value results over routines.
Generous time off: 24 vacation days, your birthday off, plus local holidays.
Tech & tools: Work on cutting-edge AI projects that power millions of devices.
Gear: Brand-new Apple MacBook Air/Pro, Apple Studio Display, and AirPods Pro 3.
Learning & development: Dedicated budget for personal and professional growth.
High impact: Your work will shape the future of vision AI.