13 of 13 Deep Learning Jobs in Central London

Machine Learning Engineer/ML Engineer Machine Learning Development Design and implement machine learning models for financial applications, with a focus on pricing and risk analytics Build scalable ML pipelines for processing large-scale financial data Develop deep learning architectures for time series prediction, anomaly … data-driven approaches to complement traditional quantitative finance models Support implementation of ML solutions for derivatives pricing and risk management Core Technical Skills Machine Learning Expertise : Deep understanding of ML algorithms (supervised/unsupervised learning, reinforcement learning) Extensive experience with neural networks, including RNNs, LSTMs, Transformers ...

Senior Machine Learning Engineer (Generative AI/LLMs) Location: Fully Remote (UK-based) Salary: £75,000 - £100,000 (depending on experience) The Role We're hiring a Senior Machine Learning Engineer to lead the design and productionisation of Generative AI and Large Language Model (LLM) applications. This role … strong influence over architecture, tooling, and the future direction of LLM-powered products. What You'll Be Doing Design, develop, and deploy advanced machine learning and deep learning models into production. Architect scalable LLMOps pipelines on GCP/Vertex AI , including fine-tuning, vector search ...

Title: Machine Learning Engineer Location: London, UK Employment Type: Full-time Department: Data Science/AI Engineering Role Overview We are seeking a highly skilled Machine Learning Engineer to design, build, and deploy scalable ML solutions that power intelligent products and services. You will work closely with data … scientists, software engineers, and product teams to transform cutting-edge research into production-ready systems. Key Responsibilities Model Development: Design, train, and optimize machine learning models for predictive analytics, NLP, computer vision, or recommendation systems. Data Pipeline Engineering: Build and maintain robust data pipelines for feature extraction, transformation ...

Urgent 12-month Hybrid AI/Machine Learning (ML) engineer role paying £400 a day inside IR35 in central London with 2-3 days in the office a week. Start before Christmas, I need to send candidates today for this to be possible. Interviews next week apply asap/… Data solutions using Hadoop, Spark, PySpark, and Data Lake architectures. Develop and deploy ML models (supervised, unsupervised, tree-based, ensemble methods). Implement deep learning architectures (CNN, RNN, LSTM) using TensorFlow, PyTorch, and Keras. Work on NLP and Generative AI tasks including embeddings, transformers (BERT, GPT), and OpenAI ...

Looking for a deep learning role that could make the Mariana trench seem like a puddle? This global investment manager hires asset class experts, such as an ex-portfolio manager from a Tier 1 hedge fund to grow and manage risk. You’re going to be part … headcount growth this year to over 1000 which includes a 20% increase into research. You’ll collaborate to develop different machine learning models for trading strategies and create high quality signals. You'll be working at an MFT systematic multi-strat fund whose performance has been top tier over ...

working with a leading international professional services firm to recruit a Data Scientist – Senior Consultant to support the delivery of innovative analytics and machine learning solutions in a fast-paced, collaborative environment. This is a fantastic opportunity to work on a diverse range of high-impact data science projects … data capabilities and delivering meaningful insights that underpin business-critical decisions. What You’ll Do Develop and deploy advanced analytics, data science, and machine learning solutions across a variety of use cases. Use technologies such as Python, R, Azure, Databricks, SQL, Power BI, and Tableau to extract actionable insights ...

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 ...

models that could be locally resident, problems in computer vision, speech, Natural Language Processing (NLP), multilingual models, applied statistics, data mining or conventional machine learning models. We look to our data scientists to be conversant with at least 2 or more of the above areas, and be conversant with … deep learning and conventional machine learning methods. Have requisite theoretical strength, and expertise in problem solving whilst being hands on and be conversant with coding in Python along with relevant libraries. Qualifications/experience: PhD/Master’s/Graduate Degree in Computer Science, Machine Learning ...

advanced analytics solutions across our client’s business in the postal service sector. Day-to-day of the role: Design, develop, and deploy machine learning models for predictive analytics, classification, clustering, and recommendation systems. Utilize Natural Language Processing (NLP) and Large Language Models (LLMs) for text analysis, sentiment analysis … Qualifications: Strong proficiency in Python, SQL , and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch . Hands-on experience with ML algorithms and deep learning architectures. Expertise in NLP techniques and frameworks, familiarity with LLM fine-tuning and deployment. Knowledge of big data technologies and cloud platforms. ...

reach of a global investment platform. Our team partners directly with internal investment desks as well as portfolio companies across industries to deliver machine learning solutions that unlock value and accelerate decision-making. Your work will range from developing and validating robust predictive models for pricing and valuation across … business value, supporting deal team members and portfolio company executives. We’re looking for data scientists who are passionate about impact—those who bring deep statistical knowledge, thrive in fast-paced environments, and want to see their models deployed, used, and making a difference. What you will do Build ...

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 ...

Cambridge Working style: Hybrid - 3 days a week in office Salary: Up to £90k Contract: 12-month FTC. Hawkwood are partnering with a pioneering deep-tech start-up who are at the forefront of AI-driven materials discovery. Our client is advancing artificial intelligence to push the boundaries … tech, advanced manufacturing, clean energy and other areas where breakthroughs can deliver meaningful environmental impact. 🌍 Founded by a world-renowned AI Professor and a deep-tech commercial leader, the business combines scientific pedigree with proven execution. The team includes some of the most cited AI and science researchers globally ...

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 ...