Hiring 3 Computer Vision Engineers: How a PE-backed logistics company in Chicago Scaled with Second Talent

The Challenge

The company operated 12 distribution centers across the Midwest. Manual package sorting and damage inspection created bottlenecks that cost them 4-6 hours of processing time daily. Their private equity backers demanded operational improvements within 18 months to hit growth targets.

Damage claims averaged $3.2M per year. Human inspectors caught only 62% of package damage before shipment. Customers received damaged goods, filed complaints, and switched to competitors. The company needed computer vision systems that could inspect packages at conveyor belt speed.

Chicago’s tech talent market offered limited computer vision expertise. Local senior engineers with OpenCV and YOLO experience commanded $180K-220K base salaries plus equity. The few candidates they interviewed lacked edge deployment experience. None had built production systems that processed 10,000+ packages per hour.

They needed developers who could build real-time detection systems, deploy models to edge devices in warehouses, and integrate with existing warehouse management software. The timeline was tight. Their PE backers expected measurable results by Q3 2025.

The Solution

Second Talent presented three senior Computer Vision Engineers based in Vietnam within 11 days. All three had 7+ years of experience building production vision systems. One had deployed YOLO models for manufacturing defect detection. Another had built real-time tracking systems for autonomous vehicles. The third specialized in edge optimization and had reduced model inference time by 73% in a previous role.

The hiring process took 19 days total. Second Talent handled technical screening, portfolio review, and live coding assessments. The client conducted final interviews focused on system design and warehouse integration challenges. All three engineers demonstrated experience with OpenCV, TensorFlow, and edge deployment frameworks.

Second Talent set up EOR services in Vietnam within 8 days. This covered payroll, benefits, tax compliance, and employment contracts. The client paid a single monthly invoice. No entity setup required. No local HR headcount needed. The team started work on March 3, 2025.

The engineers adopted an AI-native workflow from day one. They used Claude and GPT-4 to generate data augmentation pipelines, optimize model architectures, and write edge deployment code. This reduced development time by 40% compared to the client’s internal estimates. The team shipped the first damage detection prototype in 6 weeks. Full warehouse deployment happened in 4.5 months.

The Results

The damage detection system achieved 94.7% accuracy in production. It flagged damaged packages before they reached shipping docks. Annual damage claims dropped from $3.2M to $1.2M. The $2M reduction paid for the entire development team 3.8 times over in the first year.

Package sorting accuracy reached 99.2% across all facilities. The system processed 847 packages per hour per line. Warehouse throughput increased 35% without adding staff. The company handled 2,400 additional packages daily across their network. This unlocked $1.8M in new revenue capacity.

The three engineers cost $17,500 per month total through Second Talent’s EOR service. Equivalent Chicago hires would have cost $45,000 per month in salary alone, plus benefits, equity, and office space. Annual savings reached $240K. The team continued expanding the system to include warehouse navigation for autonomous forklifts and predictive maintenance for conveyor systems.

“We needed computer vision expertise that simply did not exist in our local market at a price point that made sense. Second Talent delivered three engineers who had built exactly these kinds of systems before. They were productive from week one and shipped a damage detection system that saved us $2M in the first year. The EOR setup meant we had zero administrative overhead.”

VP of Engineering