1 to 25 of 130 PyTorch Jobs in England

learning, and reinforcement learning. Proficiency in programming languages such as Python, Java, Scala or C++, and experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. Hands-on experience with data preprocessing, feature engineering, and model evaluation techniques. Strong problem-solving skills and the ability to think critically more »

LLM's is advantageous. Solid understanding of statistical analysis, hypothesis testing, and experimental design. Expertise in machine learning algorithms and frameworks (e.g., TensorFlow, Keras, PyTorch). Strong problem-solving skills and the ability to translate business challenges into data science solutions. Familiarity with version control systems (e.g., Git) and CI more »

fine-tuning foundation models for predictive tasks or embedding generation Strong experience writing code in Python, and with appropriate deep learning packages such as PyTorch, TensorFlow Experience developing, debugging, and applying deep learning models in the cloud using GPUs, ideally on AWS A pragmatic and entrepreneurial mindset, and be able more »

deployment, monitoring and maintenance of models in production desired Expertise in using and implementing cutting-edge machine learning algorithms, frameworks, and libraries, such as PyTorch, Keras, Tensorflow to solve clustering, classification, regression, and optimization problems on large scale data sets Hands-on experience with modern NLP methods required. Specifically: Transformers more »

focus on NLP, machine learning, and MLOps. Proficiency in Python and its libraries for data manipulation, analysis, and machine learning (e.g., scikit-learn, TensorFlow, PyTorch). Strong knowledge of AWS services, particularly AWS Sagemaker, and experience working within an AWS environment. Experience with large language models (LLMs) and their applications more »

Azure Synapse Analytics, etc., is a plus. of Knowledge Graphs and LLM’s is advantageous. in machine learning algorithms and frameworks (e.g., TensorFlow, Keras, PyTorch). with version control systems (e.g., Git) and CI/CD practices. ability to lead and mentor data science teams, driving collaboration and knowledge sharing. more »

problems and solid knowledge of mathematical foundations of ML algorithms. Proficiency in Deep Learning Architectures (e.g., MLP, RNN, CNN) and popular frameworks (e.g., TensorFlow, PyTorch, Keras). Expertise in multiple open-source machine learning libraries (e.g., scikit-learn, Pandas, NumPy, Matplotlib, seaborn, Spacy, NLTK, transformers, Hugging Face, pymupdf). Practical more »

closely with the Head of Data. The best-matched Senior Data Scientist would have the following experiance: Tech stack: Python, scikit-learn, pandas, Tensorflow, Pytorch, SQL, AWS Experiance in Natural Language Processing Experiance with AWS Master’s or PhD in Computer Science, or a related field, with a focus on more »

NLTK, scikit, SpaCy > Machine Learning NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) > Strong IaC experience, using Terraform or CloudFormation > Data Wrangling > Systems: Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. Senior ML Learning Engineer desirable more »

NLTK, scikit, SpaCy Machine Learning – NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) Data Wrangling Systems: Linux, APIs, infrastructure design – load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer – desirable skills: Version control (Git), computer vision libraries, Big more »

NLTK, scikit, SpaCy Machine Learning NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) Data Wrangling Systems: Linux, APIs, infrastructure design load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer desirable skills: Version control (Git), computer vision libraries, Big more »

NLTK, scikit, SpaCy Machine Learning – NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) Data Wrangling Systems: Linux, APIs, infrastructure design – load balancing, VMs, PostgreSQL, vector dbs. ML Learning Engineer – desirable skills: Version control (Git), computer vision libraries, Big more »

in natural language processing (NLP) and its applications. Solid coding level in Python programming language, with experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects. Previous experience in working on Spark, Hive, and SQL, Preferred qualifications, capabilities, and skills Financial service background PhD more »

in a scientific discipline such as Mathematics, Physics, Biology or Computer Science Be experienced in software engineering, including Python experience Have experience working with Pytorch and NumPy Ability to write technical documentation, papers, reviews and notes, and deliver technical information in a digestible format Experience developing, testing, and proving new more »

with Git in a version-controlled environment • Experience with cloud platforms desirable (Azure, AWS or GCP) • Experience working with Machine Learning libraries (scikit-learn, PyTorch) and statistical techniques is desirable You'll have an understanding of: • An enthusiastic problem-solving mindset with a desire to solve technical problems and model more »

in production at scale. Deep knowledge of machine learning algorithms applied to solving business problems. Proficiency in Python and popular Data Science frameworks (e.g. pytorch, pandas, numpy etc) and MLOps platforms (e.g. Sagemaker) Solid understanding of metrics, benchmarking and evaluation methodology AI-powered user-facing products. Experience working in highly more »

degree or equivalent qualification, or other evidence of equivalent knowledge. Professional or research experience in some of the following: ML/NLP tools like PyTorch, Scikit-learn, Transformer architecture and Neural Networks. Coding and software engineering in mainstream programming languages, such as Python. Statistical packages for data manipulation and in more »

in a tech team using a diverse tech stack including: Backend: Python, FastAPI, PostgreSQL, Vespa, SQLAlchemy, Flask. Frontend: React, Next.js. Data Science: Python, Jupyter, PyTorch, Pandas, Spacy, Huggingface, Numpy, Streamlit, Weights and biases. Infra: Pulumi, Docker, AWS AppRunner, Step Functions, Grafana cloud monitoring, Prefect. Who you are Must haves: Experience more »

NLP experience - NumPy, Pandas Commercial hands-on experience with Hugging Face and finetuning LLMs Expertise in learning algorithms, neural networks and ML frameworks (TensorFlow, PyTorch) Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure Understanding of Big Data Technologies (Hadoop, Spark etc) Experience with more »

experience – NumPy, Pandas etc. Commercial experience leveraging open-source models, finetuning LLMs & RAG pipelines Expertise in learning algorithms, neural networks and ML frameworks (TensorFlow, PyTorch etc.) MLOps experience Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure Understanding of Big Data Technologies (Hadoop, Spark more »

insurance domain , with hands-on experience across predictive modeling, natural language processing, computer vision, and reinforcement learning. Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, Java), and cloud platforms (e.g., AWS, Azure, GCP). Thorough comprehension of insurance business processes and regulatory frameworks, with the ability more »

methodologies and algorithms Expertise in popular data science platforms such as Alteryx and Python, including libraries and frameworks like NumPy, SciPy, Pandas, NLTK, TensorFlow, PyTorch, and Airflow Strong understanding of statistical analysis, encompassing distributions, statistical testing, regression, and other techniques Experience handling unstructured data sets Familiarity with software engineering principles more »

DevOps software development methodology Familiarity with CI/CD and pipeline automation Familiarity of machine learning principals/pipelines and associated toolsets such as Pytorch and Tensorflow Familiarity with Azure, AWS, GCP products and services - Knowledge of technologies including: Docker or Kubernetes Distributed version control systems such as Git Exposure more »

the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively more »

a partnership model, conveying information clearly and creates a sense of trust with stakeholders. Preferred qualifications, capabilities and skills Experience with deep learning frameworks (pytorch, tensorflow) Experience with big-data technologies (Spark, Hadoop) or distributed computation frameworks (Dask, Modin) Hands on experience with Natural Language Processing (NLP) and Large Language more »