Computer Vision Engineer

EVONA
Bristol
1 year ago
Applications closed

Related Jobs

View all jobs

Computer Vision Engineer

Computer Vision Engineer

Computer Vision Engineer - Sports Tracking

Computer Vision Engineer – Sports Tracking

Computer Vision Engineer - Sports Tracking

Computer Vision Engineer - Sports Tracking

Drones kill and injure more than 5,000 Ukrainians per month—more than any other weapon.

Our client is on a mission to stop that.


They make hand-launched missiles to neutralize short-range air threats. Small enough to carry three in a tactical vest and affordable for all ground units, our micro-missile will be the smallest, most cost-effective guided missile ever deployed.


Their goal:Turn the tide of war in Ukraine and provide NATO with a proven solution to drone threats.


We are seeking aComputer Vision Engineerto join the founding team. You’ll develop and deploy real-time vision algorithms on edge hardware to track fast-moving aerial targets. Your work will include sensor and board selection, data collection, and implementing efficient classical CV techniques to meet extreme performance and size constraints.


Responsibilities:

  • Develop and optimize real-time optical detection and tracking algorithms.
  • Deploy vision algorithms on edge hardware for low-latency performance.
  • Design and execute data collection processes to train and validate CV models.
  • Select and integrate sensors, processors, and IMUs.
  • Collaborate with a team to ensure seamless integration into the missile system.


Required Qualifications:

  • Hands-on experience with classical computer vision methods and edge deployment.
  • Experience with fast optical tracking and real-time systems.
  • Understanding of sensor and hardware platform selection.
  • Previous experience in data collection for CV applications.
  • Willingness to work from the UK.


Bonus Qualifications:

  • Experience with missile, UAV, or aerospace systems.
  • Knowledge of embedded systems and hardware optimization.
  • Experience deploying solutions on FPGAs
  • Willingness to work in safe areas of Ukraine.
  • Passion for Ukraine’s defense.
  • Startup or rapid R&D experience.


Why Join Them?

  • Impact: Develop technology to protect lives.
  • Ownership: Lead the vision systems for a groundbreaking product.
  • Purpose: Work with a team delivering frontline solutions.
  • Compensation: Competitive salary and stock options (0-2%).


They design based on soldier needs, not rigid contracts, offering agility to adapt and deliver where it matters most. If you’re ready to make an impact, join us.

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.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.