Computer Vision Engineer

As a Computer Vision Engineer at Trunk Tools, you'll be responsible for enhancing image analysis capabilities specifically within the construction domain. This includes developing computer vision models such as image classification, object detection, and segmentation while optimizing workflows to seamlessly integrate these models into existing processes. You will also be working on acquiring proprietary datasets and conducting experiments to evaluate model performance, ensuring cutting-edge solutions that address the unique challenges in construction.

To qualify for the Computer Vision Engineer position at Trunk Tools, you should have an MS/PhD in Computer Science, Computer Vision, Robotics, or a related field, alongside 5+ years of practical experience in computer vision. Proficiency in Python and familiarity with ML frameworks like PyTorch or TensorFlow is crucial, ensuring you can effectively handle image processing and visual data analysis. Experience with visual transformers and a keen interest in the construction sector are highly valued.

At Trunk Tools, we understand the importance of continuous learning and growth. As a Computer Vision Engineer, you will receive a learning and growth stipend to pursue courses or certifications that enhance your skills. Our collaborative environment encourages knowledge sharing and peer-to-peer learning, ensuring you stay at the forefront of technology while contributing to meaningful projects in the construction industry.

At Trunk Tools, you can expect a close-knit and collaborative environment. We value every team member's voice and foster a culture of inclusivity and innovation. We believe in a healthy work-life balance, offering unlimited PTO, flexible work options, and regular in-person retreats to strengthen team bonds. You’ll find that our team not only works hard but also plays hard, ensuring a fulfilling work experience.

As a Computer Vision Engineer at Trunk Tools, you could work on groundbreaking projects that involve designing workflows and agents to automate construction processes. You'll tackle complex issues such as extracting data from blueprints and site images, facilitating better project management and reducing errors in construction. Your work will directly influence innovations that propel the industry into the future.

When answering this question, highlight specific projects where you developed or implemented image classification models. Discuss the frameworks used, such as TensorFlow or PyTorch, and elaborate on challenges faced and solutions you implemented to enhance the model's accuracy, showcasing your problem-solving skills relevant to the Computer Vision Engineer role.

To answer this question effectively, outline your step-by-step approach starting from data collection and preprocessing to the choice of model architecture. Explain how you ensure robustness and accuracy, including techniques like augmentation and transfer learning to adapt to the construction domain, demonstrating your thorough understanding of the field.

Focus on discussing techniques such as hyperparameter tuning, model pruning, and regularization methods that help enhance model performance. Provide examples from previous projects where these optimizations led to tangible improvements, showing how you'll use these strategies in your role at Trunk Tools.

Address the specific challenges, like the varying quality of images, the complexity of construction blueprints, and the need for accurate feature extraction. Share how you have navigated these challenges in your previous work and discuss innovative solutions you've implemented to overcome them.

Mention your commitment to continuous learning through online courses, attending conferences, and engaging with communities. Share specific sources such as research journals, forums, or influencers you follow, reinforcing the idea that you are proactive about staying abreast of trends and innovations in computer vision relevant to your role at Trunk Tools.

Relate a specific team project where you played a crucial role in directing the computer vision aspect. Talk about how you collaborated with colleagues, facilitated communication, and contributed both technically and strategically to the project's success, demonstrating your teamwork and collaborative skills.

Be sure to mention your proficiency in languages like Python, and any relevant libraries like OpenCV or Scikit-learn. Share your experience with toolsets used in previous projects, explaining why certain languages and tools are advantageous for computer vision tasks, reinforcing your technically-skilled background.

Express your understanding of ethical concerns in technology, especially in computer vision. Discuss how you incorporate fairness and transparency in your projects, outlining steps you've taken to mitigate biases in datasets or algorithms to ensure ethical implementations of computer vision at Trunk Tools.

Provide insights into the growing role of computer vision in enhancing safety, efficiency, and productivity in construction. Showcase your enthusiasm for innovation in the industry and express how you believe Trunk Tools contributes to this exciting future, aligning your vision with the company's mission.

Share a detailed overview of a project you spearheaded, covering the initial concept, development and deployment phases, and the impact it had on users or processes. Discuss your leadership role, challenges faced, and how you overcame them, affirming your capabilities as a Computer Vision Engineer.