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Angie Z.

Dubai, United Arab Emirates

6 years experience

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Min H.

Dubai, United Arab Emirates

4 years experience

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Sohail M.

Abu Dhabi, United Arab Emirates

9 years experience

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Peng Z.

Dubai, United Arab Emirates

3 years experience

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Andrew C.

Sharjah, United Arab Emirates

7 years experience

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Xinran L.

Dubai, United Arab Emirates

5 years experience

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Interview with structure

Same questions, same rubric, every candidate. Scheduling, panels and scoring all run in one place.

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Compare scored candidates side by side, then track the offer through acceptance to the agreed start date.

About the role

Source and shortlist

Structured interview

Progression and salary

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About the role

Job Title: Computer Vision Engineer
Job Summary:
We are seeking a skilled Computer Vision Engineer to join our team and help develop cutting-edge visual algorithms and AI models. As part of our AI division, you will work on image processing, object detection, and machine learning techniques to build applications for industries such as healthcare, technology, and research. This role offers the chance to work on innovative projects and be part of a collaborative, forward-thinking team.
Requirements:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- 2+ years of experience working with computer vision technologies and machine learning algorithms.
- Proficiency in Python and frameworks such as OpenCV, TensorFlow, or PyTorch.
- Strong understanding of computer vision algorithms like image classification, object detection, and facial recognition.
- Experience in image processing and deep learning.
- Familiarity with cloud-based services for deploying AI models (AWS, Azure, Google Cloud).
Responsibilities:
- Develop and optimize computer vision algorithms for various real-world applications.
- Design and implement image processing techniques to improve the accuracy and performance of models.
- Collaborate with data scientists and machine learning engineers to build and deploy deep learning models.
- Integrate computer vision solutions into production systems and continuously improve them based on feedback and performance metrics.
- Work closely with cross-functional teams to understand project requirements and deliver solutions aligned with business goals.
- Stay up-to-date with the latest trends and advancements in computer vision and machine learning technologies.
Must-Have:
- Proficiency in computer vision libraries such as OpenCV, as well as machine learning frameworks like TensorFlow and PyTorch.
- Hands-on experience in developing and deploying deep learning models for tasks such as object detection, image segmentation, and pattern recognition.
- Strong problem-solving skills with the ability to handle complex visual data.
- Experience with programming languages such as Python, C++, or MATLAB.
- Familiarity with working in cloud environments for AI model deployment.
Soft Skills:
- Strong problem-solving and analytical thinking.
- Attention to detail, especially when handling large datasets and complex algorithms.
- Excellent communication skills to convey technical concepts to non-technical team members.
- Research skills to keep up with the latest advancements in AI and computer vision.
Hard Skills:
- Expertise in computer vision algorithms (image classification, object detection, image segmentation).
- Proficiency in machine learning and deep learning (using Python, OpenCV, TensorFlow, PyTorch).
- Experience with image processing techniques (filtering, transformation, enhancement).
- Knowledge of cloud platforms (AWS, Azure) for model deployment and optimization.

Source and shortlist

Professional network
- Leverage your professional network and reach out to former colleagues, industry peers, and tech community members to ask for referrals.
Educational Institutions:
- Top Universities with AI and Computer Vision Programs: Look at institutions known for strong AI research programs. Also, consider graduates from AI and ML-focused bootcamps.
- Online Learning Platforms: Candidates from platforms like Coursera or Udacity, which offer specialized programs in AI and computer vision, often have practical experience.
Company Career Pages:
- Use your company's career page to attract candidates who are already interested in your business and its technology projects.
Role-Specific Job Boards:
- AI Jobs Board (aijobsboard.com): Specialized in roles focused on artificial intelligence and machine learning, including computer vision.
- Stack Overflow (stackoverflow.com/jobs): A great platform to post job listings and attract developers who have a focus on computer vision.
Geography-Specific Job Boards:
- United States:
  - Indeed (indeed.com): Widely used for finding tech talent across the U.S.
  - AngelList (angel.co): Particularly useful for startups looking for AI and computer vision engineers.
- India:
  - Naukri (naukri.com): India’s leading job portal for a range of technology roles.
  - Cutshort (cutshort.io): A job board focused on AI and machine learning talent.
- UAE & KSA:
  - GulfTalent (gulftalent.com): Focuses on the Gulf region and attracts tech talent for industries like healthcare, technology, and smart cities.
  - Bayt (bayt.com): A top job portal in the Middle East for technology-related roles.
- Remote Positions:
  - We Work Remotely (weworkremotely.com): Ideal for finding candidates for remote computer vision positions.
  - Remote OK (remoteok.io): Focused on remote job opportunities for developers, including AI and computer vision professionals.

Structured interview

Question: How did you choose the pre-trained model for the object detection task, and why?
- Expected Answer: The candidate should discuss the trade-offs between different models, such as accuracy vs. speed, and why they chose a specific one (e.g., YOLO for real-time detection, SSD for balanced accuracy and speed).
- Sample Answer: "I chose YOLO because it offers real-time object detection, which is important for many applications. While models like Faster R-CNN are more accurate, YOLO’s speed is ideal for tasks that require quick decision-making."
Question: Explain the preprocessing steps you used for the images before feeding them into the model.
- Expected Answer: The candidate should explain how they resized images, normalized pixel values, and applied data augmentation techniques such as flipping or rotation to improve model generalization.
- Sample Answer: "I resized the images to 416x416 pixels to match the input size required by YOLO. I also applied random rotations and flips to augment the data and make the model more robust to different perspectives."
Question: How did you evaluate the model’s performance, and what metrics did you use?
- Expected Answer: The candidate should discuss performance metrics like precision, recall, F1 score, or mean average precision (mAP), and explain how they assessed the model’s effectiveness.
- Sample Answer: "I used mean average precision (mAP) to evaluate the object detection model. I also analyzed precision and recall to understand the balance between false positives and false negatives."

Progression and salary

Level	United States	Europe	India	UAE
Junior Computer Vision Engineer	$70,000 - $90,000	€50,000 - €70,000 (€56,200 - €78,700)	₹600,000 - ₹1,200,000 ($7,200 - $14,400)	AED 180,000 - AED 250,000 ($49,000 - $68,000)
Mid-Level Computer Vision Engineer	$100,000 - $130,000	€80,000 - €100,000 (€90,000 - €112,600)	₹1,500,000 - ₹2,500,000 ($18,000 - $30,000)	AED 280,000 - AED 350,000 ($76,000 - $95,000)
Senior Computer Vision Engineer	$140,000 - $180,000	€100,000 - €130,000 (€112,600 - €146,300)	₹2,500,000 - ₹3,500,000 ($30,000 - $42,000)	AED 400,000 - AED 500,000 ($109,000 - $136,000)
Computer Vision Lead	$180,000 - $220,000	€130,000 - €160,000 (€146,300 - €179,800)	₹4,000,000 - ₹5,500,000 ($48,000 - $66,000)	AED 550,000 - AED 650,000 ($149,000 - $177,000)
Head of AI/Computer Vision	$220,000 - $300,000	€150,000 - €200,000 (€168,900 - €224,200)	₹6,000,000 - ₹8,000,000 ($72,000 - $96,000)	AED 700,000 - AED 900,000 ($190,500 - $245,500)

customer stories

Hear from our customers

Whitecarrot’s ATS platform has made a significant impact on our recruitment process. It’s easy to use and has streamlined our interview scheduling and candidate evaluations. We’re excited to continue using it and seeing the results.

Sabrine

ZEOF Group

We’ve been using Whitecarrot for all our job openings this year, and the experience has been excellent. The platform has made our recruitment process more efficient, and everyone is happy with the results.

Karl

Careem

Whitecarrot’s ATS has been a game-changer. It’s user-friendly, streamlines recruitment, and offers responsive support. Their growth-driven approach makes it invaluable. Highly recommended!

Rasha

Bayzat

Whitecarrot’s ATS has transformed our hiring process. It’s intuitive and saves us so much time. The platform’s efficiency and excellent support have helped us manage recruitment smoothly. Highly recommend it!

John

Syncsphere

We’ve seen significant improvements in our recruitment process since adopting Whitecarrot. The platform is easy to navigate, and the support team is always responsive. It’s a game-changer for our hiring efforts!

Emily

Nexanode

Sabrine

ZEOF Group

Karl

Careem

Whitecarrot’s ATS has been a game-changer. It’s user-friendly, streamlines recruitment, and offers responsive support. Their growth-driven approach makes it invaluable. Highly recommended!