At a Glance
- Tasks: Design and train RL agents for real-world control in live operational environments.
- Company: Fast-growing AI company focused on sustainability and innovation.
- Benefits: Competitive salary, hybrid work model, and collaboration with industry experts.
- Other info: Dynamic role with opportunities to switch between research and practical engineering.
- Why this job: Shape AI's interaction with the physical world and make a global impact.
- Qualifications: Degree in engineering/physics and strong experience in reinforcement learning.
The predicted salary is between 60000 - 80000 £ per year.
If applying reinforcement learning to real physical systems excites you — not toy problems, not simulations, but live operational environments — this is a standout role.
A fast‑growing AI company is looking for an Applied Scientist to design, train and harden RL agents end‑to‑end: from problem formulation and reward design through to federated deployment and on‑site inference. You’ll work at the intersection of ML, physics and engineering, reasoning about thermodynamics and equipment behaviour just as much as architectures and training dynamics.
What you’ll be doing:
- Design + train RL agents for real‑world control
- Turn messy telemetry into ML‑ready problems
- Validate behaviour against physical principles
- Productionise models — federated training, on‑site inference, monitoring
- Support research + academic work
What you bring:
- Engineering/physics degree
- Strong RL experience (deep RL, debugging, non‑trivial problems)
- Python + modern ML stack (PyTorch/JAX, NumPy, RL libs)
- Comfortable with time‑series sensor data
- Ability to turn ambiguous operational challenges into tractable ML problems
- Happy switching between research and practical engineering
Nice to have:
- Classical control, MPC, HVAC, thermodynamics, power systems
- Simulation, digital twins, surrogate models
- GNNs, meta‑learning, offline/safe RL
- Federated learning, distributed training, edge ML
- Publications or open‑source work
- Sustainability‑focused optimisation experience
Why it’s exciting:
You’ll help shape how AI interacts with the physical world, working on systems with real sustainability impact at global scale — and collaborating with experts across ML, engineering and infrastructure to deploy physical‑AI responsibly and reliably.
Applied Scientist in London employer: DMCG Global
Join a fast-growing AI company in London, where your work as an Applied Scientist will directly impact real-world systems and sustainability. With a hybrid work model, you'll enjoy a collaborative culture that fosters innovation and professional growth, alongside competitive compensation and opportunities to engage with cutting-edge technology in machine learning and reinforcement learning. This role not only offers the chance to tackle complex engineering challenges but also to contribute to meaningful projects that shape the future of AI in operational environments.
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We think this is how you could land Applied Scientist in London
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We think you need these skills to ace Applied Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at DMCG Global, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at DMCG Global. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at DMCG Global
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
