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Quantum, Sensors, Robotics Technology Analyst – Market Research & Consultancy

🕒 April 10

IDTechEx

51 - 200

⚡ Energy

Website
LinkedIn
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Technology Analyst at IDTechEx providing market research and consultancy on emerging technologies. Engaging with innovators and clients and promoting research findings at international events.

🇬🇧 United Kingdom – Remote

💵 £33k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Robotics

🇬🇧 UK Skilled Worker Visa Sponsor

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Technical Staff Member – Robotics Research Lead

Full-stack Engineer

• Build and ship AI-native product features end-to-end
• Design and implement backend systems, APIs, and data pipelines that support model-driven workflows
• Work across the stack when needed (backend, frontend, infra, experimentation)
• Collaborate closely with researchers, designers, and product to bring ideas into production
• Own systems from design → implementation → monitoring → iteration
• Turn ambiguous goals into concrete scopes, milestones, and shipped outcomes
• Move quickly while maintaining a high bar for reliability, performance, and simplicity

Member of Technical Staff – Product Engineer

Software Engineer

• Work with model researchers to define what “good data” means for our models, including quality metrics, validation checks, and acceptance thresholds
• Explore open source datasets and create internal ones most suitable to build fundamental World Models
• Build algorithms for automated data quality assessment, data domain mixtures, and domain adaptation from synthetic to real data.
• Track datasets, metadata, provenance, and versions so experiments are reproducible and it’s clear what data went into which training and evaluation runs
• Own CI/CD and development tooling for the data stack (GitHub, Python, PyTorch), and automate repetitive workflows to reduce friction
• Track and optimize throughput, storage, and compute utilization across pipelines and related assets

Technical Staff Member – Data Intelligence

Machine Learning Engineer

• Translate cutting-edge research into production-ready machine learning systems
• Design, build, and deploy end-to-end ML models and pipelines
• Develop and optimize models for image and video processing
• Own the full ML lifecycle: experimentation, training/fine-tuning, evaluation, and deployment
• Build low-latency, real-time inference systems and scalable ML infrastructure
• Rapidly prototype using open-source models and adapt them for product needs
• Conduct experiments, analyze results, and iterate to improve performance
• Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale
• Stay current with advancements in machine learning and apply them to continuously improve products