Computer Vision Team Lead - Space Robotics & Autonomy

Holt Executive
Oxford
3 months ago
Applications closed

Related Jobs

View all jobs

Computer Vision Engineer

Machine Learning Engineer

Machine Learning Engineer – Founding Team (Computer Vision / GenAI)

Lead Data Scientist

Lead Data Scientist

Computer Vision & AI Engineer — Advanced Defense Tech

Are you an experienced Computer Vision engineer ready to take the next step in your career? This is an opportunity to lead a high-performing Computer Vision & Robotics team developing real-time image processing and autonomy software for spacecraft and ground systems.

You’ll play a key role in advancing technologies that enable close-proximity operations and on-orbit servicing, designing algorithms for object detection, tracking, and pose estimation in some of the most challenging environments imaginable.

What You’ll Do

Leadership & Team Development

Lead a team of Computer Vision engineers, providing technical guidance and mentorship.
Oversee project delivery, ensuring quality, performance, and timely execution.
Collaborate with GNC, Software, and Systems teams across multiple mission projects.
Foster innovation and continuous learning within a collaborative engineering culture.Technical Responsibilities

Design and implement computer vision modules for spacecraft navigation and autonomy.
Develop and benchmark algorithms for pose estimation, tracking, and visual perception.
Deliver efficient, high-quality CV software suitable for real-time and safety-critical applications.
Contribute to simulation, verification, and validation of vision-based navigation systems.
About You

Degree (BSc/MSc) in Computer Science, Software Engineering, Robotics, or similar.
5+ years of hands-on experience in computer vision algorit...

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.