1 to 25 of 236 Permanent Keras Jobs in England

Direct message the job poster from Dabster At Dabster, we specialize in connecting top talent with leading global companies. We are currently seeking an experienced Gen AI Architect to join our client's team in London, UK . Our mission More ❯

language models (LLMs) and prompt engineering for business applications. Strong programming skills ( Python, R, Java ) for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep understanding of enterprise AI architecture, data engineering, and model optimization . Strong problem-solving skills More ❯

language models (LLMs) and prompt engineering for business applications. Strong programming skills ( Python, R, Java ) for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep understanding of enterprise AI architecture, data engineering, and model optimization . Strong problem-solving skills More ❯

language models (LLMs) and prompt engineering for business applications. Strong programming skills ( Python, R, Java ) for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep understanding of enterprise AI architecture, data engineering, and model optimization . Strong problem-solving skills More ❯

TensorFlow, AI Foundry, OpenAI, Scikit-learn etc.). • Solid understanding of core machine learning concepts • Hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch, Keras). • Proven understanding of software engineering principles, data structures, algorithms, and design patterns. • Experience with version control systems (e.g., Git). • Excellent problem-solving and analytical skills. • Strong communication and More ❯

of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using More ❯

of the mathematics of CNNs and GANs essential, or other advanced deep learning techniques. Proven experience in developing and deploying deep learning models using frameworks such as TensorFlow, PyTorch, Keras, or similar. Strong proficiency in programming in Python. Excellent problem-solving skills and the ability to work independently as well as in a team. Strong communication skills with the ability More ❯

strong competencies in data structures, algorithms, and software design. Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience working with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano). Strong coding skills in Python and familiarity with ML/DL libraries like TensorFlow, PyTorch, or JAX. Knowledge of data analytics concepts, including data warehouse technical More ❯

projects involving models like GANs, VAEs, transformers, or diffusion models Proficiency in programming languages such as Python, R, or Julia, and experience with ML frameworks like TensorFlow, PyTorch, or Keras Strong understanding of deep learning architectures, neural networks, and statistical modeling techniques Experience with cloud platforms (AWS, Azure, Google Cloud) and MLops tools for model deployment and management Excellent problem More ❯

Spark. Preferred Will be curious, enjoy problem solving and have empathy for the problems you are challenged with Working knowledge on data science frameworks and toolkits (Scipy, Scikit-Learn, Keras, PyTorch, Etc.) Experience with Git, Databricks and Microsoft Azure technical stack Prior exposure to Agile methodologies Experience building large scale machine learning systems Master's Degree in Computer Science, Data More ❯

scale using SQL in Redshift/BigQuery. Good problem solving and analytical skills. Ability to learn and adapt to newer ML technologies. Exposure to deep learning stack (PyTorch/Keras/TensorFlow) and techniques (Representation/Transfer Learning, RNN/LSTM, Transformers). Experience working with Big Data in a cloud based production environment (AWS/GCP/Azure). More ❯

and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills – Good to have: • Expertise in any one framework (TensorFlow, Pytorch, Keras) • Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning, conversational AI, and natural language processing frameworks.) • Experience More ❯

role, with hands-on experience in data science engineering. Proficiency in programming languages such as Python and SQL. Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn. Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques. Familiarity with data visualization tools such as Power BI. Solid understanding of statistical analysis More ❯

modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, ResNets, VAEs, GANs, Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using More ❯

role, with hands-on experience in data science engineering. Proficiency in programming languages such as Python and SQL. Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn. Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques. Familiarity with data visualization tools such as Power BI. Solid understanding of statistical analysis More ❯

Spark. Preferred Will be curious, enjoy problem solving and have empathy for the problems you are challenged with Working knowledge on data science frameworks and toolkits (Scipy, Scikit-Learn, Keras, PyTorch, Etc.) Experience with Git, Databricks and Microsoft Azure technical stack Prior exposure to Agile methodologies Experience building large scale machine learning systems Master's Degree in Computer Science, Data More ❯

role, with hands-on experience in data science engineering. Proficiency in programming languages such as Python and SQL. Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn. Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques. Familiarity with data visualization tools such as Power BI. Solid understanding of statistical analysis More ❯

Requirements Experience: 3-5 years of hands-on experience in AI and machine learning. Technical Expertise: Strong proficiency in Python. Expertise in machine learning frameworks such as TensorFlow, PyTorch, Keras, or similar. Machine Learning: Solid understanding of supervised and unsupervised learning, deep learning (CNNs, RNNs, GANs), and reinforcement learning. Data Handling: Proficient in data manipulation and analysis using tools like More ❯

computing, high-performance computing, neural deep learning methods, and/or machine learning. Experience in using Python and hands-on experience building models with deep learning frameworks like TensorFlow, Keras, PyTorch, MXNet. PREFERRED QUALIFICATIONS PhD or Master's degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. Practical experience in solving complex problems in an More ❯

role, with hands-on experience in data science engineering. Proficiency in programming languages such as Python and SQL. Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn. Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques. Familiarity with data visualization tools such as Power BI. Solid understanding of statistical analysis More ❯

Creative problem-solving and solution scoping Strong grasp of mathematical, statistical concepts, and machine learning algorithms Proficiency in Python and data science libraries for example NumPy, Pandas, Scikit-learn, Keras SQL proficiency Experience with cloud environments for example Google Cloud Platform Version control management Ability to work efficiently without compromising quality Effective communication and data storytelling skills Collaborative mindset and More ❯

AI Engineer About Company Cyber Infrastructure is #1 Technology solution provider, committed to delivering outstanding client experiences and optimal career growth for its team members. Established on November 7, 2003, Cyber Infrastructure (CIS) is a CMMI Level 5 accredited organization. More ❯

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field You have strong proficiency in Python, leveraging libraries like Prophet, TensorFlow, Keras, and PyTorch for LSTM, along with expertise in SQL and machine learning frameworks You have hands-on experience with leading time series forecasting techniques, including Prophet, ARIMA, and LSTM, enabling More ❯

and public sector clients, including participating in RFI/RFP processes, preparing bids, and delivering presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions on Cloud platforms (AWS, Azure, Google Cloud) using provisioning tools like Terraform. Proven ability to deploy technologies such as Docker, Kubernetes, CI More ❯

RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. Terraform). Technology deployment– proven More ❯