You are ready to delve into the world of automation and have chosen the path of a Computer Vision Engineer. This exciting role consists of learning highly advanced technologies, something today's employers are looking for. It's a career path that will lead you to work across multiple industries.

Getting Through the Door

Since you want to become a computer vision engineer, there are certain entry-level steps you must learn in order to land a job. Knowledge of methods on how to acquire, analyze, process and understand digital images is a necessity. Familiarity with the programming language Matlab along with deep learning architectures and having machine learning skills is also a part of the process of getting ahead in this career. You can find outlets to help you succeed on your own through platforms like Udacity and Coursera. There are also organizations like DataKind where you can meet amongst your peers to practice and grow your skills.

Other technical skills that can improve your chances include experience with OpenCV, as well as Convolutional Neural Networks (CNNs). You should be adept in math, such as with linear algebra and calculus. Python, Java, C++ and other programming languages are important to know since they are widely used for image processing. Some other minimum requirements for an entry- or junior-level computer vision engineer position include:

• Developing image analysis algorithms and deep learning architectures to solve problems
• Designing and creating platforms for image processing and visualization
• Knowledge of computer vision frameworks and libraries
• Understanding of TensorFlow or PyTorch for dataflow programming
• Some software engineering experience
• Writing clean and re-usable code
• Can work well in an agile team environment
• Have strong analytical skills and the ability to learn with minimal oversight

Degrees and Experience

Companies look for computer vision engineers to have a bachelor's or higher in computer vision, computer science, mathematics, machine learning or other related fields. Employers may also seek interns who are earning their undergrad or graduate degrees to learn and develop needed skills while on the job. Having a few years of experience managing and manipulating data sets, as well as using UNIX/Linux command line tools and scripts are helpful. Companies will look for individuals who can build their own complex image captioning models. Good analytical, communication, mathematical and interpersonal skills are also important.

Working as a Junior-Level Engineer

As a junior-level engineer, you will be comfortable working in a team environment. You possess experience with linear and non-linear optimization. Being familiar with 2D and 3D computer graphics along with IoT platforms is a plus. You will be tasked with analyzing, designing, developing and debugging software for advanced computer vision and image classification systems. Junior-level engineers in this field will also be acquainted with cloud-based applications and visual system hardware, such as a structured-light 3D scanner.

Moving Up the Ranks

One of the exciting aspects of being a computer vision engineer is the different subfields for the skill set. You may decide to focus on applications for machine vision systems or artificial intelligence (AI). You can learn more about how computer vision can be applied to robots along with the modeling, segmentation, tracking and detection aspects involved. You may build up your skills in constructing software systems for VR (Virtual Reality) and AR (Augmented Reality) experiences. The medical industry is an attractive place for computer vision engineers to gain insight on multi-dimensional and video sequences for the technologies used in that sector.

Advance Your Career: How to become a Senior Computer Vision Engineer

Senior Computer Vision Engineers are tasked with taking the lead in designing, analyzing and developing high-performance systems. Collaborating with a team of developers and others to get projects completed is a main part of the job. They will research algorithms in order to come up with innovative solutions, as well as improve and optimize models. A company may also task them with identifying and managing market opportunities for vision-related products along with leading user training programs and participating in project reviews.

Study the Core Fields

As a computer vision expert, you need to be highly skilled in your field. You have to stay up-to-date on emerging technologies and the latest publications for research. Proficiency with deep learning platforms like TensorFlow and Caffe, as well as programming languages is a requirement. Having a solid foundation with data structures, distributed and parallel programming, 3D point cloud processing, software debugging, optimization, prototyping and benchmarking is also important.

Invest in Yourself

You have demonstrated highly sought after skills as a senior computer vision engineer to employers. You can source, curate, process and interpret large volumes of data with no problem. It also helps to show that you have gained knowledge in using parallel computing, OpenCL and GPGPU. Mapping, LiDAR perception and sensor fusion are also key attributes you can hone. Besides having the required tech expertise, you will need strong leadership, technical writing, communication and presentation skills.

Don't Stop at Computer Vision

You can further accelerate your career by obtaining an advanced degree in fields such as artificial intelligence and electrical engineering. Becoming a CVP (Certified Vision Professional) and obtaining other certifications will help you along the way. You should also try gaining more insight into newer technologies to increase your appeal to employers.

Computer Vision Engineer Job Description

We’ve done the research for you. After evaluating numerous job descriptions, we’ve written our own representative job description for a mid-level computer vision engineer with between 2 and 5 years of relevant experience.

As a computer vision engineer, you are able to automate various functions that the human visual system can do. You can multitask and work efficiently in a collaborative setting on critical projects to get them done. Our computer vision engineers are self-motivated and display leadership qualities. We welcome diversity and encourage healthy debate and discussion.

What We Need Your Help With

• Researching and developing scalable computer vision and machine learning solutions for complex problems
• Collaborate in cross-functional teams to integrate image analytics algorithms and software, as well as develop system prototypes
• Proficiency with vector quantization and clustering to build search engines and systems
• Understanding of computational geometry, statistics and linear algebra
• Maintain and develop software modules for large-scale image and LiDAR data processing in the cloud
• Analyze and improve the efficiency and stability of various deployed systems
• Work well in a collaborative team environment

What We Look For

• 3+ years of experience with computer vision, deep learning and machine learning
• 2+ years experience with programming languages like Java, Scala, C++, Matlab and Python
• Experience with Unix and Linux command line tools and scripts
• Experience in OpenCV or other computer vision libraries, as well as deep learning frameworks like TensorFlow
• Experience with point cloud meshing, SLAM frameworks, image segmentation and 2D marker tracking
• Experience with three dimensional (3D) imaging concepts
• Strong knowledge of PCA and other machine learning models for facial recognition
• Proficiency with CNNs (Convolutional Neural Networks) and RNNs (Recurrent Neural Networks)
• Strong background in object-oriented design, testability and reusability
• Excellent analytical, mathematical, communication and problem-solving skills
• Keeps up with the latest advancements in technology related to the field
• B.S., M.S. or Ph.D. in computer science, computer vision, machine learning or other related fields

These Would Also Be Nice

• Experience with optimizing algorithms for embedded devices using OpenGL and OpenCL
• Experience with JIRA, Git and agile project management
• Experience with WebRTC, ARM and CUDA
• Experience with Mathematica and Maple languages

Senior Computer Vision Engineer Career Paths: Where To Go From Here

The use of computer vision engineers has expanded within companies around the world. This hi-tech field has helped to pave the way to an increase in automated experiences for people in general throughout their everyday lives. You, as a senior computer vision engineer, have accumulated 10 years of experience and are now looking further into the future. Companies such as GE, LG Electronics, Apple and Amazon have computer vision teams dedicated to creating products to improve the user's experience.

Senior Computer Vision Engineers can easily transition into machine learning and ultimately become Senior Machine Learning Engineers. This role involves building machine learning models at scale using distributed platforms like Spark or Hadoop. There's also the title of Senior Data Scientist which entails tasks such as developing predictive models, as well as evaluating complex issues and resolving business challenges with analytic solutions. Another career path is that of the Senior Software Architect who is responsible for assuring the architectural integrity of programs and software applications. Another position could be that of an Engineering Director in which you are in charge of managing and coordinating all the engineers in a company to get projects completed. There are also the roles of IT Director, Chief IT Architect, Software Engineering/Development Director and Chief Technology Officer (CTO) that may suit your late career goals.

The positions listed generally require a master's degree with a Ph.D. being an employer's preferred choice. Managerial and industry certifications along with years of expertise are a must-have on this journey. You will also need to possess not only excellent communication skills but be able to lead effectively and make important decisions for the company as a whole.