Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist

Reading
1 day ago
Create job alert

Data Scientist

Are you passionate about pushing the boundaries of Machine Vision? We’re looking for a talented Data Scientist specialising in Machine Vision or Spatial Analysis to develop, train, and deploy advanced image and video detection models across EO, IR, near-IR, and multi-band data sources.

You’ll work at the forefront of deep learning and classical computer vision, designing solutions for challenging real-world applications including small and distant object detection, multi-modal fusion, and real-time performance optimisation.

Key Responsibilities



Design, train, and optimise detection and classification models using deep learning and classical computer vision techniques.

*

Manage and prepare large-scale imagery datasets, including labelling, augmentation, and quality checks.

*

Develop algorithms for multi-spectral and fused EO/IR/near-IR data.

*

Validate, benchmark, and refine models for deployment in real-time or embedded environments.

*

Collaborate with engineering teams to integrate, deploy, and maintain production-grade vision models.

Requirements

*

Strong expertise in machine vision, including CNNs, transformer-based architectures, and classical CV methods (OpenCV, scikit-image).

*

Proficiency in Python and key ML/vision libraries (PyTorch, TensorFlow, NumPy, SciPy, scikit-learn).

*

Experience designing models for detection/classification (YOLO, Faster R-CNN, RetinaNet, ViT, EfficientNet).

*

Hands-on experience with imagery across EO, IR, and/or multi-band datasets.

*

Solid understanding of machine learning fundamentals, training workflows, and evaluation metrics.

*

Master’s/Ph.D. in Computer Vision, Machine Learning, Data Science, Applied Mathematics, or related field, plus 2–5 years’ relevant experience.

Soft Skills

*

Strong analytical mindset with exceptional problem-solving abilities.

*

Clear communication and documentation skills.

*

Proactive, collaborative, and comfortable working in a fast-paced, research-driven environment

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.