21 of 21 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 ...

Clearance: SC Cleared Package: Up to £100,000 base + benefits The Opportunity We’re looking for a Principal Data Science Consultant who combines deep technical capability with a strong consulting mindset. You’ll help clients unlock the value in their data, applying advanced AI, ML, and mathematical modelling … trusted advisor to clients – helping them define their digital vision, identify opportunities, and translate data science into tangible value. Design and implement machine learning , deep learning , and large language model (LLM) solutions for real-world business challenges. Bring strong mathematical reasoning and estimation skills to build robust ...

will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will … work together with a team of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, Vision and Language Models), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks ...

seeking a Senior Deep Learning Engineer to build the future of Embodied AI . This is a role for those who work 'in the weeds' of model architecture and training loops not API wrappers or prompt engineers. The Mission Architect Behavior: Own the development of motor policies using … weak-supervision , and curate high-quality datasets. Failure Analysis: Systematically identify and solve failure modes through retraining loops. Technical Requirements Experience: 3+ years in deep learning (shipped models, research papers, or major OSS). Domain Depth: Hands-on expertise in VLMs , Diffusion/Generative Video ...

Senior Machine Learning Engineer - London Join the analytics team as a Machine Learning Engineer in the insurance industry, where you'll design and implement innovative machine learning solutions. This permanent role in London offers an exciting opportunity to work on impactful projects in a forward thinking environment. … Client Details Senior Machine Learning Engineer - London This opportunity is with a medium-sized organisation in the insurance industry. The company is committed to utilising advanced analytics and machine learning to enhance its services and deliver value to its clients. Description Senior Machine Learning Engineer - London This ...

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 ...

seeking a Senior Deep Learning Engineer to build the future of Embodied AI . This is a role for those who work 'in the weeds' of model architecture and training loops not API wrappers or prompt engineers. The Mission Architect Behavior: Own the development of motor policies using ...

global investment platform. Our team partners directly with internal investment desks as well as portfolio companies across industries to build and deploy machine learning systems that accelerate decision-making and unlock business value. You’ll design, implement and deploy production-grade AI and ML systems, ranging from NLP pipelines … models not just trained, but deployed, adopted, and driving measurable results. What You’ll Do Design and deliver AI systems: Build and deploy machine learning models and data-driven products that directly impact investment decisions and portfolio company performance. Drive measurable impact: Partner with internal desks and portfolio teams ...

push the boundaries of AI integration in cloud services. Thought Leadership and Client Engagement • Provide architectural guidance to clients on incorporating GenAI and machine learning into their cloud[1]native applications and architectures. • Conduct workshops, briefings, and strategic dialogues to educate clients on AI benefits and applications, building strong … Technologies: Proficiency in Python, Java (and/or Golang), and Spring; expertise in AWS, Azure, Google Cloud; Kubernetes and containerization. • AI Expertise: Advanced machine learning algorithms, GenAI models (e.g., GPT, BERT, DALL-E, GEMINI), NLP techniques. • Big Data: Experience with Hadoop and Spark. • Ethics: Knowledge of AI ethics ...

insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate … advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field ...

dynamic, high-energy environment. Join our team and help shape the future of Vision AI. 🌎 Location and Legalities This full-time Machine Learning Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics … does not provide visa sponsorship. 🚀 What You'll Do As a Machine Learning Engineer at Ultralytics, you will be at the forefront of developing and refining our world-class Ultralytics YOLO models. You will work on the entire lifecycle of our models, from research and development to high-performance ...

contribute to long-term technical direction About You: Proven experience building and shipping production AI systems (not just prototypes) Strong foundations in machine learning and deep learning principles Hands-on experience with LLMs, agents, RAG systems, or large-scale inference pipelines Comfort moving between research papers ...

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 ...

developing models for strategic content valuation. Multi-objective balancing and long term measurement. We rely extensively on state-of-the-art ML around personalization, deep learning, causal inference, optimization, ranking and recommendation. What You’ll Do Within the Sharechat AI team, we are looking for an experienced Staff … Spark, Databricks and stream data processing such as Kafka, RedPanda is a plus. Direct experience in building and applying large-scale (100M+ users) machine learning solutions for personalizing recommendations. Hands-on experience building training frameworks and/or serving large-scale models using tools such as Tensorflow or PyTorch ...

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 ...

Reinforcement Learning (RL) Engineer Manipulation London Based (5 days in office) Competitive salary A high-profile robotics organization is urgently seeking a high-caliber RL Engineer (Manipulation) to join their London-based R&D team. This role is pivotal in bridging the gap between simulation and real-world application … behavior cloning. High-Performance Engineering: Designing and profiling research-grade PyTorch/JAX code to support large-scale, distributed RL infrastructure. Essential Skills Needed Deep Learning Mastery: 5+ years building and shipping models, with deep hands-on expertise in LLMs, VLMs, or generative architectures. Industry Experience: 3+ ...

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 ...

global community of developers and researchers. 🛠️ Skills and Experience 5+ years of experience in software engineering, with a strong focus on AI and Machine Learning (ML). Expert-level proficiency in Python and deep learning frameworks, particularly PyTorch. Proven experience building and deploying applications with LLM APIs … Apple Display provided. Team: Become part of a supportive and passionate team environment. If you are driven to redefine the capabilities of machine learning and eager to make a significant impact, Ultralytics offers an exceptional career opportunity. ...

research findings at leading NLP/ML/AI conferences and in top journals. Qualifications: 1. Currently in the PhD degree in NLP, Machine Learning, or a related area, or recently submitted the thesis; available at least three days per week (with the supervisor and university approval). 2. … tier NLP/ML conference or journal (e.g., ACL, NAACL, EMNLP, EACL, NeurIPS, ICLR, ICML). 3. Hands-on experience with Python and deep learning libraries, especially PyTorch, Hugging Face, and Transformers. 4. Experience in one or more of the following areas: supervised fine-tuning of LLMs ...

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 ...

including 1000s of A100s), 100s of petabytes of storage, and almost 10 petabytes of RAM. This cutting-edge infrastructure supports state-of-the-art Deep Learning models that process trillions of data points, driving trading algorithms that handle $300 billion across 80+ exchanges daily. They ...