Reinforcement Learning Scientist

Stealth AI Startup
Liverpool
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist - Optimisation

Postdoctoral Fellow- Computational Biology and Machine Learning

Postdoctoral Fellow- Computational Biology and Machine Learning

Machine Learning Engineer (RL)

Deep Learning Researcher

Join Us: Research Scientist - Online Reinforcement Learning (RL) at an Agentic AI Start-Up!


Are you ready to revolutionize the future of intelligent agents? We're anAgentic AI start-upon a mission to build the next generation of autonomous systems capable of real-time learning, adaptation, and decision-making. If you’re passionate aboutOnline Reinforcement Learningand want to shape the frontier of AI, we’d love to hear from you!


About Us


We are a well-funded, ambitious, fast-growing start-up buildingAI agentsthat can learn, adapt, and thrive in dynamic, interactive environments. Our vision is to empower businesses and individuals with cutting-edge, agentic AI solutions that redefine how machines interact with the world.


The Role


As aResearch Scientist in Online Reinforcement Learning, you will:

  • Innovate: Develop groundbreaking algorithms for real-time learning and decision-making in dynamic, multi-agent systems.
  • Collaborate: Work closely with a team of researchers and engineers to create scalable solutions that deliver real-world impact.
  • Experiment: Lead experimental projects to address challenges like stability, data efficiency, and exploration in online RL.
  • Productize AI: Translate research insights into deployable AI systems for robotics, gaming, autonomous platforms, and more.
  • Share Knowledge: Publish research at top-tier conferences (e.g., NeurIPS, ICML, ICLR) and contribute to the global AI community.


What You’ll Bring


  • PhD or equivalentin Machine Learning, Reinforcement Learning, Computer Science, or related fields.
  • Expertisein RL algorithms (e.g., PPO, A3C, DQN) and their application to dynamic environments.
  • Proven Research Impact: Strong publication record in top conferences/journals and a passion for advancing AI.
  • Technical Skills: Proficiency in Python, RL frameworks (PyTorch/TensorFlow), and cloud-based ML tools.
  • Start-Up Mindset: A proactive, problem-solving attitude and a love for tackling challenges in fast-paced environments.
  • Visionary Thinking: A deep interest in agentic AI and its potential to transform industries.


Why Join Us?


  • Impactful Work: Shape the future of agentic AI in industries like autonomous vehicles, robotics, and intelligent systems.
  • Ownership: Be part of a start-up where your ideas and contributions directly drive our success.
  • Cutting-Edge Tech: Access to the latest tools, resources, and computational infrastructure.
  • Growth Opportunities: Thrive in a collaborative, growth-focused culture that values curiosity and innovation.
  • Start-Up Perks: Competitive salary, meaningful equity, flexible work options, and a chance to grow with us.


Our Mission


At our core, we’re driven by the belief that intelligent agents can reshape the way we live, work, and explore. Join us on our journey to build a future where AI systems are not just tools but partners in discovery and creation.

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

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

🍪 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.