National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning & Reinforcement Learning Lead

Opus Recruitment Solutions
City of London
4 days ago
Create job alert

Hot Opportunity Alert!
Salary: £120,000 - £150,000
Central London Office

I’m thrilled to be working with one of the most exciting robotics R&D companies out there ✨

We’re looking for a Senior Engineer with deep expertise in reinforcement learning to help drive the development of intelligent, full-body motion capabilities. This role is ideal for someone passionate about building robust, real-world solutions for dynamic locomotion and manipulation in complex environments.

Key Responsibilities:
Design and implement learning-based control strategies for advanced locomotion tasks such as walking, balancing under load, stair climbing, and fall recovery.
Develop high-fidelity simulation environments that reflect real-world dynamics, including actuator constraints and environmental interactions.
Conduct rigorous testing in both simulated and physical environments to ensure performance and reliability.
Collaborate with multidisciplinary teams to integrate control systems into a unified robotic platform.

Required Experience & Skills:
MSc or PhD in Robotics, Control Engineering, Machine Learning, or a related field.
3+ years of experience developing control systems for legged robotic platforms.
Strong background in reinforcement learning applied to robotic control.
Deep understanding of humanoid robot dynamics and control theory.
Proven experience with deploying algorithms on physical robots, including hardware-in-the-loop testing.
Strong programming skills in Python and C++.
Familiarity with hybrid control systems that combine classical and learning-based approaches.

Bonus Skills:
Experience with real-time control systems and minimizing latency in robotic applications.
Knowledge of trajectory optimization and motion planning under uncertainty.
Exposure to collaborative or multi-agent robotic systems.
Understanding of safety-critical control strategies and system-level fault tolerance.

Related Jobs

View all jobs

Junior Machine Learning Engineer - AI startup

Machine Learning Engineer (PhD)

Machine Learning Engineer (PhD)

Machine Learning Engineer

Research Engineer, Machine Learning (Horizons) London, UK

Head of Machine Learning

National AI Awards 2025

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.

LinkedIn Profile Checklist for AI Jobs: 10 Tweaks That Triple Recruiter Views

In today’s fiercely competitive AI job market, simply having a LinkedIn profile isn’t enough. Recruiters and hiring managers routinely scout for top talent in machine learning, data science, natural language processing, computer vision and beyond—sometimes before roles are even posted. With hundreds of applicants vying for each role, you need a profile that’s optimised for search, speaks directly to AI-specific skills, and showcases measurable impact. By following this step-by-step LinkedIn for AI jobs checklist, you’ll make ten strategic tweaks that can triple recruiter views and position you as a leading AI professional. Whether you’re a fresh graduate aiming for your first AI position or a seasoned expert targeting a senior role, these actionable changes will ensure your profile stands out in feeds, search results and recruiter queues. Let’s dive in.

Part-Time Study Routes That Lead to AI Jobs: Evening Courses, Bootcamps & Online Masters

Artificial intelligence (AI) is reshaping industries at an unprecedented pace. From automating mundane tasks in finance to driving innovation in healthcare diagnostics, the demand for AI-skilled professionals is skyrocketing. In the United Kingdom alone, AI is forecast to deliver over £400 billion to the economy by 2030 and generate millions of new jobs across sectors. Yet, for many ambitious professionals, taking time away from work to upskill can feel like an impossible ask. Thankfully, part-time learning options have proliferated: evening courses, intensive bootcamps and flexible online master’s programmes empower you to learn AI while working. This comprehensive guide explores every route—from short tasters to deep-dive MScs—showcasing providers, course formats, funding options and practical tips. Whether you’re a career changer, a busy manager or a self-taught developer keen to go further, you’ll discover a pathway to fit your schedule, budget and goals.