1 to 25 of 68 TensorFlow Jobs in the UK excluding London

Graphs and 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. more »

Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database, and Cosmos DB. Understanding of CI/ more »

pandas, 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 more »

Mlflow, Promptflow, Azure OpenAI, Azure Synapse Analytics, etc., is a plus. Knowledge Graphs and LLM’s is advantageous. Machine learning algorithms and frameworks (e.g., TensorFlow, Keras, PyTorch). Version control systems (e.g., Git) and CI/CD practices. Ability to lead and mentor data science teams, driving collaboration and more »

pandas, 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 more »

pandas, 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 more »

pandas, 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 more »

NLP 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 more »

highly skilled professionals. Requirements : Proficiency in Python, including libraries such as numpy, pandas, and scikit-learn Experience with deep learning frameworks (PyTorch, JAX, Keras, Tensorflow) Strong theoretical understanding of machine learning and neural networks Experience with containerized processes (Docker, Kubernetes) Familiarity with cloud services and distributed computing frameworks (AWS more »

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 to more »

and receiving guidance from senior leadership. Key Responsibilities for a Machine Learning Engineer: Develop and debug code in Python, utilizing deep learning frameworks like TensorFlow 2 and Keras Perform in-depth data analysis tasks and design new neural architectures Participate in code reviews, maintain codebase quality, and ensure feature more »

MongoDB and Docker Experience in Julia and different programming paradigms Experience in Jira or similar project management tools Experience with NumPy, SciPy, NetworkX, Pandas, TensorFlow, or similar scientific computing libraries Experience with Qiskit, Cirq, pyQuil, or other open source quantum software frameworks Familiarity with developing GPU-accelerated software in more »

machine learning models for business application Experience in applied research PREFERRED QUALIFICATIONS Experience with modeling tools such as PyTorch, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. Experience in building speech recognition, machine translation and natural language more »

and relevant experience working as an Machine Learning Engineer/AI Engineer Strong foundation in Python Excellent knowledge of ML libraries and frameworks like TensorFlow, PyTorch, Keras and scikit-learn. Experience with neural network architectures, deep learning techniques, and building and training deep learning models. Creating and handling large more »

ecosystem (Lab, Notebook) and related libraries and tooling. • Python libraries for data management, statistical analysis, machine learning, and visualisation. • Machine learning frameworks such as TensorFlow and PyTorch. • Knowledge of Natural Language Processing and Computer Vision applications. • Strong understanding of basic probability concepts. • In-depth knowledge of the machine learning more »

and stream processing. Experience with or at least an interest in Machine Learning and widely used technologies, such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and PyTorch. Knowledgeable about key MLOps concepts such as CI (including data aspects), CD (specific to ML), CT (Continuous Training), feature stores, automated CI more »

Scala, C#, or Java, and adeptness with cloud SDKs and APIs. Deep understanding of AI/ML to enhance pipeline efficiency, with experience in TensorFlow, PyTorch, AutoML, Python/R, and MLOps platforms like MLflow and Kubeflow. Solid background in DevOps , including CI/CD automation with Bitbucket Pipelines more »

machine learning Experience supporting cloud platforms – AWS preferred IaC and container orchestration environments – Kubernetes preferred Experience working with Machine Learning technologies and methodologies – PyTorch, Tensorflow etc Experience with Python packages for data manipulation – Pandas, Numpy Salary for this role is up to £75,000, plus bonus, fantastic benefits and more »

the planet for the better. Tech Stack: Python GNU/Linux Mathematical + Scientific Libraries (Numpy etc..) Azure NumPy, SciPy, Matplotlib, Pandas, Scikit-learn, TensorFlow, PyTorch, scikit-learn, Keras, matplotlib, seaborn, plotly, bokeh, Altair, Django, Flask, requests, BeautifulSoup, Jinja2 Humand Talent Solutions and their clients and associates do not more »

you: 5+ years experience in software engineering or data science with a focus on machine learning Experience in the python library - Pytorch, Pandas, Numpy, Tensorflow, Scikit-learn Experienced working in a microservice-based architecture# Experience working with Docker or Kubernetes Strong interest in ML and keeping up to date more »

in Computer Science, Mathematics or similar At least 3 years of industry experience working on deep learning models applied to embedded systems C++ programming TensorFlow, PyTorch Desired experience Java, Kotlin What’s on offer Competitive base Excellent bonus scheme 25+ days holiday Hybrid working And much more Interested? This more »

work with our AR solutions. Solid background in machine learning and AI, particularly in an AR setting. Proficiency in utilising machine learning frameworks like TensorFlow, PyTorch, and programming languages such as Python, Java, and C++. Demonstrated capability in leading and overseeing a team of developers. Bachelor's or Master more »

ecosystem (Lab, Notebook) and related libraries and tooling. • Python libraries for data management, statistical analysis, machine learning, and visualisation. • Machine learning frameworks such as TensorFlow and PyTorch. • Knowledge of Natural Language Processing and Computer Vision applications. • Strong understanding of basic probability concepts. • In-depth knowledge of the machine learning more »

development and deployment. Excellent communication and teamwork skills, capable of collaborating effectively with non-technical colleagues. Strong knowledge of Python and ML libraries (PyTorch, Tensorflow, Keras, etc.) with R/SQL knowledge, partnered with experience with MLOps tools (Kubernetes, Docker, Jenkins, etc.) would be advantageous. Strong knowledge and experience more »

testing, deployment, and vigilant monitoring. Expertise in C#, Python, and the tools and libraries that make AI magic happen like Semantic Kernel, Langchain, Keras, TensorFlow, Pytorch, etc. Experience in creating and delivering multi-tenant cloud solutions at scale using Docker, Kubernetes and Cloud services. Experience with Azure stack will more »