1 to 25 of 74 TensorFlow Jobs with Hybrid or WFH Options

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 »

Machine Learning, or a related field. Experience in AI/Machine Learning research and development. Proficiency in Python. Experience with popular machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Experience with using NVIDIA GPUs for fine tuning AI models Strong mathematical and statistical background. Excellent problem-solving and critical more »

relevant to AI and GPU computing. Strong understanding of GPU architecture, CUDA programming, and parallel computing principles. Familiarity with AI frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience in deploying AI models at scale, such as transformer-based NLP models, graph-based deep learning models, and/or 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 »

General & Specialist Knowledge Strong technical skills, proficient in various programming languages, frameworks, and tools for data analysis ad AI development, such as Python, R, TensorFlow, PyTorch, Scikit-learn, etc; Familiar with various data sources, formats, and standards, such as APIs, JSON, XML, CSV, etc, and detail orientated; Experience in more »

or a related field. Strong background in deep learning, with hands-on experience in developing and implementing deep neural networks using frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in programming languages such as Python and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn). 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 »

analysing results and creating insights Proficiency in software development (Python, Github, Jupyer Notebooks, etc.) Proficiency with deep learning packages (such as PyTorch, Jax, or TensorFlow) Experience with ML/LLM Software packages (e.g. HuggingFace, wandb, numpy, matplotlib, NLTK, etc.) Good problem-solving and communication skills Ability to work in 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 »

proficiency in Python ( 3+ years professionally ) and are comfortable with a range of libraries including Pandas, scikit, NumPy etc. as well as PyTorch/TensorFlow and, ideally, cloud-based architecture (AWS/GCP/Azure etc.) You are experienced in building computational models and deploying them into production Experience more »

learning experiments on clinical datasets. You will get to work with some of the most innovative tools in the market, including scikit-learn, pandas, Tensorflow, Pytorch, spaCy, and the AWS data stack. The role is hybrid, in central London (zone 1) and they are offering more »

Person: *Strong Python skills *ML experience *Energy or Geospatial Data experience *GCP or AWS experience *Pandas and SQL experience *Scikit-learn, Keras, Pytorch, or TensorFlow experience *Full rights to work in the UK Reference Number: BBBH225262 To apply for this role or for to be considered for further roles 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 »

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 »

analysis, optimise algorithms, publish white papers and mentor team members. Experience : Strong experience with cloud data and ML services. Proficiency in deep-learning frameworks (TensorFlow, PyTorch, etc.) & basic libraries for data science e.g. NumPy, Pandas, Scikit-Learn Strong command of standard data science techniques - supervised/unsupervised ML, Bayesian more »

Strong 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 more »

transformer technologies etc.) Experience in deploying NLP pipelines to production Python experience including data science libraries (scikit-learn, pandas, NumPy) and deep learning frameworks (Tensorflow, Pytorch) Desirable Experience with virtual agent platforms such as IBM Watson or DialogFlow Team leading experience Proven experience in CI environments, unit testing, automatic 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 »

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 »