COMPUTER VISION SCIENTIST SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Updated: Dec 24, 2024 - The Computer Vision Scientist has extensive experience in object detection and pattern recognition project development within the retail sector. Skilled in building large-scale image recognition systems and designing products with machine learning at scale, writing production-ready Python code, and understanding Convolutional and Recurrent Neural Network models. Strong analytical skills and team spirit ensure successful project completion.
Essential Hard and Soft Skills for a Standout Computer Vision Scientist Resume
- Object Detection
- Pattern Recognition
- Machine Learning
- Image Recognition
- CNNs
- RNNs
- Python Coding
- Data Analysis
- Algorithm Development
- Software Engineering
- Analytical Thinking
- Problem Solving
- Collaboration
- Teamwork
- Communication
- Adaptability
- Attention to Detail
- Time Management
- Creative Thinking
- Results Orientation
Summary of Computer Vision Scientist Knowledge and Qualifications on Resume
1. BS in Computer Science with 2 years of Experience
- Experience in object detection, pattern recognition-related project development.
- Experience with machine learning projects in retail
- Experience in building and maintaining a large-scale image recognition system.
- Experience with designing products that leverage machine learning at scale.
- Familiar with at least one or more deep learning frameworks: Caffe/Caffe2, TensorFlow, PyTorch.
- Skilled at writing production-ready python code.
- In-depth understanding of different Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) based models
- Analytical and problem-solving skills
- Team spirit and ability to work collaboratively with colleagues
- Results-oriented with an ability to own deliverables through to completion
- Experience and knowledge of retail and consumer product goods
2. BS in Electrical Engineering with 4 years of Experience
- Deep understanding of classic SLAM pipeline such as feature extraction, triangulation, BA, loop closure, etc.
- Familiarity with recent advances in various SLAM topics, such as visual place recognition, long-term localization, semantic SLAM, topological mapping, distributed and incrementally learned maps, etc.
- Ability to transfer conceptual models to working code in C++ or Python
- Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents
- Strong publication record in visual SLAM, computer vision or machine learning
- Experience in Deep Learning frameworks such as TensorFlow or Pytorch.
- Familiarity with vehicle sensors and hardware, including cameras, LiDAR, GPS, CAN, IMU, USB, Ethernet.
- Extensive hands-on experience in real-world robotics applications and robot operating system (ROS).
3. BS in Mathematics with 5 years of Experience
- Experience in at least one of the following areas: computer vision, machine learning/deep learning, image and video processing, computational photography, and video quality, Camera 3A, or in shipping related products to customers.
- Strong C++ developing skills and OpenCV, Eigen, GPU shaders. Experience with TensorFlow, PyTorch, or related deep learning frameworks
- Interest in computational photography and multi-media post-processing.
- Experience computational photography or ISP (3A and image enhancement algorithms) development, and in shipping related products to customers.
- Experience in development, optimization and parallelization of algorithms in multi-processor environment Experience including ARM, ARM NEON and GPU based architectures and APIs, such as CUDA, OpenCl, OpenGL(ES) or familiar with Qualcomm DSP developing and HVX , Halide, or other functional languages.
- Experience with camera automatic control algorithm development implementation (i.e. auto white balance, auto focus, auto exposure, auto flicker detection/correction, video stabilization, auto scene detection).
- Experience with at least one category of Multi-view geometry, simulation, graphics rendering Alignment, Registration, Stereo Vision, Robotics, Machine Learning, Deep Learning, Image and Video quality
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