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For Companies At a Glance
- Tasks: Design and deploy cutting-edge computer vision models to enhance user experiences.
- Company: Join a fast-growing start-up poised for significant impact in the tech industry.
- Benefits: Enjoy share options, competitive benefits, and the chance to shape the future of technology.
- Why this job: Be part of an innovative team driving advancements in machine learning and computer vision.
- Qualifications: Master’s degree or equivalent experience in Computer Science with 5+ years in computer vision.
- Other info: Diversity is valued; we welcome applicants from all backgrounds.
The predicted salary is between 43200 - 72000 £ per year.
We are currently recruiting on behalf of a leading start-up business set for significant growth for the role of Senior Computer Vision Engineer. This is a rare opportunity to join an ambitious, fast-scaling company at a pivotal stage.
What you’ll be doing:
- Design, build, and deploy Large Vision Models (LVMs) to enhance customer experiences, improve workforce efficiency, and boost product performance.
- Collaborate with data engineers to gather, preprocess, and curate large visual datasets, ensuring robust and high-quality data pipelines.
- Optimise model architectures and tune hyperparameters to maximise throughput while maintaining computational efficiency.
- Work closely with software engineers, product managers, and platform engineers to deliver seamless computer vision solutions.
- Monitor deployed models by analysing performance metrics, troubleshooting issues, and implementing updates to maintain optimal results.
- Stay up to date with the latest machine learning and computer vision advancements, applying new techniques to strengthen solutions and drive innovation.
Main Skills/Requirements:
- Master’s degree in Computer Science, Data Science, or a related field — or equivalent practical experience, with a strong focus on machine learning.
- Over 5 years of experience deploying computer vision models in production environments.
- Advanced proficiency in Python programming.
- Hands-on experience with cloud platforms such as AWS or GCP, and familiarity with deployment tools like Docker and Kubernetes.
- Solid understanding of computer vision techniques, including image classification, object detection, and segmentation.
- Experience with Large Vision Models (LVMs) is highly desirable.
- Proficient in SQL and skilled in working with large-scale datasets for data processing and manipulation.
How you’ll be rewarded:
- Share Options
- Competitive Benefits
- Opportunity to join a leading start-up
This is an excellent opportunity for an experienced Senior Computer Vision Engineer to join a growing company, that are driven towards success!
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Contact Detail:
Addition Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Computer Vision Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in computer vision and machine learning. This will not only help you during interviews but also demonstrate your passion for the field and your commitment to staying updated.
✨Tip Number 2
Network with professionals in the computer vision community. Attend relevant meetups, webinars, or conferences to connect with others in the industry. This can lead to valuable insights and potential referrals for the position.
✨Tip Number 3
Showcase your hands-on experience with Large Vision Models (LVMs) through personal projects or contributions to open-source initiatives. Having tangible examples of your work can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss specific challenges you've faced in deploying computer vision models and how you overcame them. This will highlight your problem-solving skills and practical experience, which are crucial for this role.
We think you need these skills to ace Senior Computer Vision Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in computer vision and machine learning. Emphasise your proficiency in Python, cloud platforms, and any hands-on experience with Large Vision Models (LVMs).
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for computer vision and your understanding of the company's goals. Mention specific projects or achievements that demonstrate your ability to design and deploy models effectively.
Showcase Relevant Projects: Include a portfolio or links to projects that illustrate your experience with deploying computer vision models. Highlight any work with data pipelines, model optimisation, and collaboration with cross-functional teams.
Highlight Continuous Learning: Mention any recent courses, certifications, or conferences you've attended related to machine learning and computer vision. This shows your commitment to staying updated with industry advancements.
How to prepare for a job interview at Addition
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Large Vision Models and other computer vision techniques. Bring examples of projects you've worked on, especially those involving image classification, object detection, or segmentation, to demonstrate your expertise.
✨Demonstrate Collaboration Experience
Since the role involves working closely with data engineers and software teams, be ready to share examples of how you've successfully collaborated in past projects. Highlight your communication skills and ability to work in a team environment.
✨Stay Updated on Industry Trends
Research the latest advancements in machine learning and computer vision before your interview. Being able to discuss recent developments or techniques can show your passion for the field and your commitment to continuous learning.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice explaining your thought process when troubleshooting model performance issues or optimising architectures, as this will showcase your analytical skills.
