The Role We are looking for a motivated Computer Vision Engineer to help build the next generation of cloud/edge-based vision systems for wildfire detection and environmental monitoring. In this role, you will work alongside experienced AI researchers and engineers to develop, evaluate, optimize, and deploy computer vision models on both cloud and edge devices. You will gain hands-on experience across modern computer vision, edge AI, embedded systems, and real-world AI deployment. Beyond wildfire detection, you will contribute to a variety of AI/computer vision projects, including vegetation detection, asset recognition, instance segmentation, scene understanding, spatial reasoning, and speech recognition. We value curiosity, adaptability, and a willingness to learn new technologies and tackle diverse technical challenges as our products evolve. This is an excellent opportunity for an engineer who enjoys learning across the entire AI stack and wants to grow into a senior technical contributor. What you'll do

• Assist in developing computer vision models for:
• Wildfire smoke detection
• Vegetation detection and classification
• Asset detection and recognition
• Instance and semantic segmentation
• Scene understanding and spatial reasoning
• Assist in developing speech recognition models for fire-related radio communications
• Help implement and maintain machine learning and computer vision pipelines.
• Assist with deploying and optimizing AI models on NVIDIA Jetson and other edge platforms.
• Support model optimization efforts, including TensorRT conversion, quantization, and inference acceleration.
• Build tools for data processing, visualization, benchmarking, evaluation, and monitoring.
• Conduct experiments, analyze model performance, and present findings to the team.
• Debug inference, deployment, networking, and hardware integration issues.
• Contribute to continuous learning, model evaluation, and data quality improvement workflows.
• Collaborate closely with AI researchers, software engineers, hardware engineers, and product teams.
• Document experiments, engineering decisions, and best practices.
• Take on a variety of technical challenges as needed and continuously expand your skills across computer vision and cloud/edge AI.

What you'll bring Required

• BS or MS in Computer Science, Electrical Engineering, Robotics, or a related field.
• 1-3 years of experience (including internships or research) in software engineering, machine learning, or computer vision.
• Experience with Python and deep learning frameworks such as PyTorch.
• Understanding of machine learning fundamentals and modern computer vision techniques.
• Familiarity with Linux development environments.
• Strong problem-solving skills, curiosity, and a desire to learn.
• Excellent communication and teamwork skills.

Preferred

• Experience with NVIDIA Jetson, CUDA, TensorRT, ONNX, or embedded AI platforms.
• Experience with OpenCV.
• Experience with one or more of the following:
• Object detection
• Instance or semantic segmentation
• Image classification
• Multi-object tracking
• Video understanding
• Speech recognition
• Familiarity with vision foundation models such as SAM, Grounding DINO, or DINO is a plus.
• Experience with cloud platforms, MLOps, or CI/CD workflows.
• Interest in deploying AI systems in real-world environments, particularly outdoor vision systems.

Final compensation for regular full-time employees is determined by a variety of factors, including job-related qualifications, education, experience, skills, knowledge, and geographic location. In addition to base salary, regular full-time roles are eligible for equity. Benefits are tailored to local market standards and statutory requirements in the employee's country of employment, and may include health coverage, retirement or pension contributions, and paid time off. Specific benefit details will be shared during the interview process.