6 of 6 Remote/Hybrid Deep Learning Jobs in Central London

Deep Learning Engineer About the Company Join a fast-growing AI-driven technology company that’s modernising prediction and decision systems for complex, real-world industries. The organisation builds powerful AI platforms that help partners, particularly in travel and transportation - automate commercial decisions, optimise revenue and personalise customer … experiences through deep learning-based forecasting and analytics. With an emphasis on bridging legacy infrastructure with cutting-edge data science, the company’s solutions provide real-time insights, dynamic pricing, and revenue optimising recommendations across large, intricate datasets. Nearly hundreds of global partners rely on this platform ...

permanent position with candidates required to do hybrid working in either Cambridge or London. Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with … helping us build the next generation of foundation models Responsibilities: Develop and refine RLHF algorithms for large language and generative models. Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment. Train, fine-tune, and evaluate LLMs and diffusion models ...

fantastic visualisation layer for analytics, making complex insights accessible and actionable. Key Skills and Experience NLP Mastery Proficiency in LLMs and transformer architecture. Deep understanding of traditional NLP techniques. Data & Visualisation Solid grasp of data visualisation tools (Tableau, Power BI, Cognos, etc.) Proficiency in Python visualisation libraries (Matplotlib, Seaborn. … cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques ...

About the role I’m working with a well-funded early-stage BioAI startup applying machine learning to a hard, underexplored biological problem with real implications for climate resilience and food security. They’re building an ML-first platform where research doesn’t sit in isolation. Models are expected … scientists, and influence real experimental decisions. They’re looking for an ML Engineer who: Has a strong grounding in modern ML (generative models, representation learning, geometric deep learning, etc.) Has expertise in building and managing ML infrastructure for large-scale training, inference, and deployment Has worked with ...

coaches, and performance staff to understand requirements and translate them into actionable data solutions Stay up to date with advancements in sports analytics, machine learning, and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack … Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building ...

agents into real-world applications. • Write clean, efficient, and testable Python code. • (Optional) Apply data science techniques to train and fine-tune ML or deep learning models. Required Skills: • Strong proficiency in Python and related libraries. • Experience with agentic AI architectures and autonomous AI agents. • Hands-on experience ...