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

Apply Now

Senior Software Engineer - AI/ML Knowledgebase

Humanoid
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer, Machine Learning Services (MLS)

Senior Software Engineer, Data & Machine Learning

Senior Software Engineer, AI/Machine Learning - EA SPORTS FC

Senior Software Engineer, Machine Learning

Machine Learning Evaluation Engineer

Computer Vision Tech Lead

At Humanoid we strive to create the world's leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity. In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries. The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do. We believe that providing a universal basic income will eventually be a true evolution of our civilization. As the demands on our built environment rise, labour shortages loom. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed. By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs. Responsibilities - Build and optimize a robust knowledge base infrastructure to support various functionalities of the humanoid robot. - Collaborate with data scientists, AI researchers, and other engineers to integrate the knowledge base with broader AI/ML frameworks. - Conduct thorough testing and validation of the knowledge base to ensure accuracy and reliability. - Stay current with advancements in knowledge representation, semantic technologies, and related fields. - Provide technical support and troubleshooting for knowledge base-related issues. - Ensure compliance with data privacy and security standards in the knowledge base system. - Present progress, challenges, and solutions to senior leadership and incorporate their feedback. Expertise - Proven experience as a software engineer with a focus on knowledge base systems, knowledge representation, or similar areas. - Proficiency in programming languages such as Python, Java, or C++. - Experience with semantic technologies, ontologies, and related tools (e.g., OWL, RDF, SPARQL). - Strong understanding of data structures, algorithms, and database management systems. - Excellent problem-solving skills and the ability to develop innovative solutions for complex problems. - Strong communication and collaboration skills, with experience working in cross-functional teams. - Familiarity with AI/ML frameworks and tools, such as TensorFlow, PyTorch, and others. - Knowledge of industry trends and best practices in knowledge management and AI. Benefits - High competitive salary. - 23 calendar days of vacation per year. - Flexible working hours. - Opportunity to work on the latest technologies in AI, Robotics, EdTech, MedTech and others. - Startup model, offering a dynamic and innovative work environment.

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.

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

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.