1 to 25 of 484 Keras Jobs in the UK

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 More ❯

Engineering, Mathematics, or a related field 5+ years of experience in AI and machine learning and deep learning model development/frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost Strong programming skills in languages such as Python, R, Java, C++, and/or MATLAB Knowledge, Skill and Abilities: Proven experience utilizing More ❯

ECS, EC2, S3, Athena, Glue). Strong problem-solving and teamwork skills. Leadership and mentorship abilities. Highly Desirable Skills Experience with deep learning libraries (Keras, PyTorch, TensorFlow). Knowledge of data processing tools (Pyspark, Hive) and databases (MongoDB, SQL, NoSQL). NLP expertise (nltk, SpaCy), especially with unstructured financial data. More ❯

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 More ❯

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 More ❯

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 More ❯

field. Proficiency in programming languages such as Python, R, or Java. Strong understanding of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). Excellent problem More ❯

data structures, parsing, optimization, data mining, parallel computing, neural networks, and machine learning. Hands-on experience with Python and deep learning frameworks like TensorFlow, Keras, PyTorch, MXNet. Knowledge of machine learning libraries such as scikit-learn, NumPy, Pandas, MLlib. Strong data engineering, communication, and presentation skills. PhD or Master's More ❯

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 More ❯

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 More ❯

/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 More ❯

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 More ❯

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. More ❯

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 More ❯

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. More ❯

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 More ❯

etc Experience in using ML tools such as Mlflow for model lifecycle management Experience with common ML libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn Familiarity with timely engineering and large language models (LLM) is a plus Proficiency in multiple programming languages Understanding of containerization technologies like Docker More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark) Strong knowledge of the main deep-learning frameworks such as PyTorch, TensorFlow, Keras Experience with Linux and shell scripting and experience with LaTeX Solid understanding of traditional data science techniques and experience with data engineer pipelines for big More ❯

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 More ❯