Senior Computer Vision Engineer

Oxford
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Embedded Linux Engineer

Senior AI/ML Engineer

Senior Electronics Engineer

Senior IT Engineer

Senior Quantitative Analyst

Senior Optical Engineer

Are you enthusiastic about pushing the boundaries of space technology and ready to contribute to a mission with global impact?

Holt Executive are currently partnered with a global leader in Space and Satellite sustainability, a dynamic and rapidly growing technology innovator who are making hugely positive contributions to tackle the growing problem of orbital space debris.

They are seeking a Senior Computer Vision Engineer to join their team of Computer Vision specialists in addressing mission-critical challenges that depend on a highly advanced Computer Vision subsystem. This technology is essential for enabling spacecraft to execute complex tasks like rendezvous, proximity operations, and docking with uncontrolled, often unpredictable objects.

As part of the global team, the successful Senior Computer Vision Engineer will oversee all aspects of the Computer Vision subsystem, including algorithms, simulations, and hardware. Your responsibilities will include designing and prototyping Computer Vision algorithms for their missions and supporting validation and testing efforts.

Key Responsibilities for the Senior Computer Vision Engineer:

Design and develop novel computer vision algorithms for space object detection and tracking, and 6 Degrees of Freedom pose estimation for space applications.
Support CV hardware procurement for missions.
Contribute to CV verification & validation planning and execution.
Support the CV subsystem test activities including hardware-in-the-loop.
Support the integration and testing of CV software implementation.
Support the CV hardware procurement activities working collaboratively with vendors and supplier chain management engineers.
Collaborate with other engineering disciplines (Systems, Guidance Navigation and Control (GNC), Flight Dynamics, etc.) in the planning, design and development of missions/systems to ensure software and hardware performance and compatibility. 
Key Skills and Experience for the Senior Computer Vision Engineer:
Essential -

Degree level knowledge of an engineering, scientific or mathematical discipline, or equivalent science based/engineering experience.
Experience in mixing image data from different sources; real and synthetic.
Firsthand experience designing and developing CV Solutions
Experience with some, or all, of -
Industrial Experience with Computer Vision Applications
Detection, Tracking and Classification methods.
Programming languages such as Python, C/C++
Version Control systems (Git)Desirable -

Master’s or PhD in Computer Vision, Machine Learning, or relevant field
Experience in space applications.
Experience with Lidar-based CV application.
Experience with ML and deep learning frameworks like PyTorch. 
Company Benefits

Opportunity to work with a highly talented, diverse & dynamic international team with cutting edge technology.
Flexible working around core hours, and 9 day working fortnight (optional).
Hybrid working available (dependent on individual role requirements).
25 days holiday (increasing yearly up to a maximum of 28 days) + 8 days Bank Holiday.
Life insurance and long-term sick pay.
Private healthcare.
Relocation allowance.
Visa sponsorship for employees considered.
State of the art office, and cleanroom facility. 
If your skills and experience match this exciting Senior Computer Vision Engineer opportunity, we encourage you to apply now

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.