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

Apply Now

Controls Engineer

London
1 year ago
Applications closed

Related Jobs

View all jobs

Security Engineer III - Data Engineer

Data Engineer

Senior Data Engineer

Data Engineer

Machine Learning Engineer

Data Engineer - Management Services

Job Overview:

We’re looking for a skilled Controls Engineer to develop and improve control systems for our innovative heating technology. You’ll be responsible for integrating machine learning models to optimise energy efficiency and reliability, helping shape the future of home heating.

Key Responsibilities:

  • Design and refine control algorithms for energy-efficient heating systems.

  • Simulate and validate system performance to ensure reliability.

  • Implement safety controls to prevent faults or inefficiencies.

  • Collaborate with software, hardware, and data science teams.

  • Test and improve control systems to meet high standards of accuracy and user satisfaction.

    Requirements:

  • Degree in Control Systems Engineering, Robotics, or a related field.

  • 3+ years of experience in control systems development.

  • Strong programming skills (Python, C/C++) and experience with control algorithms.

  • Familiarity with machine learning, IoT, and system integration.

  • A problem-solving mindset and a passion for sustainability.

    Benefits:

  • Competitive salary and equity.

  • Hybrid working model.

  • Opportunities for professional growth and development

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.

Jobs

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.

Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.