We are seeking a Computer Science or Computer Engineering graduate for an engagement deploying AI-driven computer vision for industrial safety, working alongside our data and AI engineering team and the client's controls engineers on real, on-site deliverables.
Responsibilities- Install, configure and calibrate smart cameras at manufacturing sites for human detection in restricted areas
- Train, optimize and deploy object detection models on edge hardware (AXIS ACAP)
- Build and maintain the containerized software stack on Linux, managed through GitOps workflows (Git as source of truth, automated build/test/deploy)
- Collaborate with controls engineers to translate detection events into machine signals (e.g., stop a machine when a person is too close) and validate end-to-end behavior
- Monitor model performance in the field, collect edge cases and iterate on datasets and models, with growing autonomy over the engagement
Minimum Requirements- Bachelor's degree (completed or final year) in Computer Science, Computer Engineering, Electrical Engineering, or a related field
- Strong foundation in programming fundamentals; proficiency in Python, working knowledge of C/C++
- Solid Linux background (command line, services, logs, networking basics)
- Hands-on experience with Docker (images, Compose, volumes, container troubleshooting)
- Familiarity and experience with Git-based CI/CD and GitOps practices
- Coursework or project experience in computer vision / deep learning
- Willingness to travel regularly to client manufacturing sites
Preferred Qualifications- Experience with CV/DL frameworks (PyTorch, TensorFlow, OpenCV) and object detection models (YOLO, SSD, or similar)
- Experience optimizing models for edge devices (TFLite, ONNX, quantization) on hardware such as AXIS ACAP, NVIDIA Jetson, Coral or Raspberry Pi
- Basic understanding of industrial controls (PLCs, digital I/O, Modbus, OPC-UA) and machine safety concepts
- Experience with IP cameras, video streaming (RTSP) or network configuration
- Prior internship, research, or hands-on hardware/IoT project experience
- Strong communication skills; comfort working directly with client engineering teams
The base compensation range for this full-time position is between $100,000-$120,000 plus benefits. Compensation decisions are supported through market data, where regional variances may exist based on cost of labor. We also consider prior experience, relevant skills, education, training, certifications, and other job-related qualifications. If you have questions regarding compensation, the talent acquisition team can provide details during the interview process.
