1 to 25 of 50 Keras Jobs in England

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 ❯

experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs 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 ❯

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 ❯

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 ❯

including supervised and unsupervised learning on image and tabular data. Familiarity with some of the latest AI frameworks and libraries, such as TensorFlow, PyTorch, Keras, etc. Programming skills: Experience with scripting languages such as Python for data analysis and machine learning applications and software development. Data management skills: Proficiency in More ❯

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 More ❯

life cycle (sdlc) and agile/iterative methodologies. Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions More ❯

Experience communicating across technical and non-technical audiences - Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet - Fluency in written and spoken English Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to More ❯

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. More ❯

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 More ❯

Linux, Docker. Plus, a strong opinion on your IDE/editor of choice is welcome ;) Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential. Excellent communication skills; both in customer-facing and internal team communication. Knowledge of MLOps is More ❯

techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond the day job Nice-to-haves: NLP, OpenCV, Generative AI More ❯

Experience communicating across technical and non-technical audiences. Experience in using Python and hands-on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet. Fluency in written and spoken Hebrew and English. Preferred Qualifications Proven knowledge of Generative AI and hands-on experience of building applications with More ❯

and how they operate. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative models from data in a More ❯

Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate consideration More ❯

Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate consideration More ❯

including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g. TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy and maintain production-grade Machine Learning systems. You're willing to champion best practices in code More ❯

including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g. TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy and maintain production-grade Machine Learning systems. You're willing to champion best practices in code More ❯

complex ideas simply, and work well in cross-functional teams Tech You'll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure (or similar cloud platforms More ❯

methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Understanding of More ❯

methods using both quantitative and qualitative metrics. ·Strong mathematical and statistical background. ·Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. ·Experience and understanding of mixed technical teams such as engineering, architects, business analysts. ·Familiar with MLOps industry best practices. ·Understanding of More ❯

methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Understanding of More ❯