Technical Solutions Architect I -- Computer Vision Specialist

Summary

World Wide Technology is a technology integrator that helps organizations design, build, and scale intelligent AI, digital, cybersecurity, cloud, and infrastructure solutions. The Technical Solutions Architect I will apply deep computer vision and machine learning expertise to customer opportunities, define solution architectures, and support opportunity qualification, proofs of concept, demos, partner engagement, and practice development.

Responsibilities

• **Computer vision solutioning.** Apply computer vision expertise to customer opportunities across the modern toolkit: classical computer vision, deep learning, video intelligence, spatial understanding, and vision language models. Translate a business problem such as safety, quality, throughput, or asset monitoring into a defined use case, the cameras and sensors it needs, the data required, the model approach, the integrations, and the metrics that will judge success
• **Computer vision machine learning.** Guide model selection and approach for tasks such as classification, detection, segmentation, tracking, and pose estimation, including when to use pretrained or foundation models, fine tune, or train custom models. Advise on dataset curation, annotation, and synthetic data, and on how models will be evaluated, optimized for edge deployment, monitored for drift, and retrained over time
• **Opportunity qualification and solution design.** Work with customers to gather technical requirements and develop a high level design that addresses their desired outcome
• **Proofs of concept and demos.** Design, build, and run proofs of concept and demonstrations in the ATC and AI Proving Ground, including work on edge hardware. Be clear about what a proof of concept proved, what it did not, and what it would take to reach production
• **Business case.** Connect the solution to measurable outcomes such as cost, quality, throughput, and risk
• **Partner engagement.** Evaluate and work with WWT’s computer vision partners and ISVs, and NVIDIA and Intel technologies, so recommendations are neutral and defensible
• **Enablement and content.** Share your expertise with sellers and solution architects so more of the team can carry computer vision conversations, and contribute research articles, demos, and collateral that build WWT’s presence in the market
• **Practice development.** Contribute ideas on repeatable use cases and potential offerings

Skills

• Bachelor's degree in Computer Science, Engineering, Robotics, or a related field
• Substantial hands on experience designing, training, and deploying computer vision models for real business problems, plus customer facing work in consulting, presales, or solution architecture
• Candidates should be able to describe solutions they personally built, including the cameras and sensors, data sources and labeling approach, model choices and training approach, integrations, failure scenarios, deployment approach, and the metrics used to measure success
• Depth across classical methods, deep learning, and vision language models, with judgment about when each is the right tool. Hands on experience with frameworks and tooling such as PyTorch, OpenCV, and NVIDIA TAO Toolkit
• Fluency in metrics such as precision, recall, mean average precision, and latency, and in error analysis that explains why a model fails in a particular environment
• Data collection, annotation, synthetic data, training, validation, deployment, monitoring for drift, and retraining
• Detecting events, activities, and anomalies across live and recorded video
• Running and optimizing vision workloads on edge hardware such as NVIDIA Jetson, using techniques such as quantization and TensorRT, and understanding the tradeoffs among edge, on premises, and cloud inference
• Strong discovery and communication skills, able to translate technical concepts for business audiences and represent WWT credibly in the room
• Understands how opportunities qualify and progress, and can partner with sellers as a business peer
• Comfortable in a developing practice, self directed, and collaborative
• Advanced degrees or relevant AI, machine learning, or computer vision certifications
• NVIDIA Metropolis, DeepStream, and video search and summarization
• Intel Scenescape
• Familiarity with digital twin and simulation environments such as NVIDIA Omniverse and Isaac
• Spatial intelligence and 3D scene understanding
• Working knowledge of robotics
• Experience building demos with AI assisted development tools
• Prior presales experience with a technology integrator or consultancy

Qualifications

Must Haves

• Bachelor's degree in Computer Science, Engineering, Robotics, or a related field
• Substantial hands on experience designing, training, and deploying computer vision models for real business problems, plus customer facing work in consulting, presales, or solution architecture
• Candidates should be able to describe solutions they personally built, including the cameras and sensors, data sources and labeling approach, model choices and training approach, integrations, failure scenarios, deployment approach, and the metrics used to measure success
• Depth across classical methods, deep learning, and vision language models, with judgment about when each is the right tool. Hands on experience with frameworks and tooling such as PyTorch, OpenCV, and NVIDIA TAO Toolkit
• Fluency in metrics such as precision, recall, mean average precision, and latency, and in error analysis that explains why a model fails in a particular environment
• Data collection, annotation, synthetic data, training, validation, deployment, monitoring for drift, and retraining
• Detecting events, activities, and anomalies across live and recorded video
• Running and optimizing vision workloads on edge hardware such as NVIDIA Jetson, using techniques such as quantization and TensorRT, and understanding the tradeoffs among edge, on premises, and cloud inference
• Strong discovery and communication skills, able to translate technical concepts for business audiences and represent WWT credibly in the room
• Understands how opportunities qualify and progress, and can partner with sellers as a business peer
• Comfortable in a developing practice, self directed, and collaborative

Nice to Haves

• Advanced degrees or relevant AI, machine learning, or computer vision certifications
• NVIDIA Metropolis, DeepStream, and video search and summarization
• Intel Scenescape
• familiarity with digital twin and simulation environments such as NVIDIA Omniverse and Isaac
• spatial intelligence and 3D scene understanding
• working knowledge of robotics
• experience building demos with AI assisted development tools
• prior presales experience with a technology integrator or consultancy

Benefits

• Health (Medical & Prescription), Dental, and Vision Care
• Onsite Health Centers (MO & IL)
• Employee Assistance Program
• Wellness program
• Profit Sharing
• 401k Plan with Company Matching
• Life and Disability Insurance
• Flexible Spending Accounts
• Tuition Reimbursement
• PTO & Holidays
• Parental Leave
• Medical Leave
• Military Leave
• Bereavement
• Day of Caring
• Family Planning Benefits
• Nursing Mothers Benefits
• Voluntary Legal
• Voluntary Supplemental Accident/Illness/Hospital
• Voluntary ID Theft
• Pet Insurance
• Employee Discount Program