76 to 100 of 141 Permanent TensorFlow Jobs

Proven expertise in crafting, deploying, assessing, and optimising ML models Robust engineering background complemented by proficiency in at least one ML framework such as TensorFlow or PyTorch Experience with Python or Kotlin Familiarity with CI/CD pipelines, Git, and related tools Exceptional self-organisation and problem-solving aptitude more »

their more complex ETL and advanced analytics functions, e.g. Time Series Processing. They soon plan to integrate other approaches, including native distributed PyTorch/Tensorflow, Spark-based distributor libraries, or Horovod. TECH STACK: Python, Flask, Redis, Postgres, React, Plotly, Docker. Temporal; AWS Athena SQL, Athena & EMR Spark, ECS Fargate … progressing on critical path, both individually and as a team NICE TO HAVES Distributed machine learning (Spark distributors, Horovod, native distributed on PyTorch or Tensorflow) Productionisation experience on multiple clouds Familiarity with MLOps principles and practices, and their application in a production setting COMPENSATION/BENEFITS : £100k salary (or more »

their use of Artificial Intelligence (AI). You will get to expand your network while working with cutting-edge tools in the market including TensorFlow, LangChain, LlamaIndex, and working on the development of ML, NLP and GenAI solutions. The role is hybrid, based in central London (max 1-hour … AI solutions Team leading and project management experience Extensive experience with Python, JavaScript or R Hands-on work with AI-related tools such as Tensorflow, PyTorch, LangChain or LlamaIndex Stakeholder management and ability to communicate with non-technical stakeholders regarding AI concepts Looking to grow your career further towards more »

of the associated long-term risks and ethical considerations. Technologies: AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »

Theory, or related field with a strong focus on AI/ML. Extensive hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, MXNet, JAX, and proficiency in programming languages like Python. Solid understanding of deep learning architectures, neural network design, and optimization techniques for efficient model more »

Scripting). - Strong experience with UNIX operating system, particularly the command line interface. - Demonstrable experience in common AI/ML frameworks such as PyTorch, TensorFlow, OpenNN. - Knowledgeable in different types of neural networks and other ML techniques, including Gaussian Processes, confidence measures, clustering techniques, and application of neural networking 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 »

Linux, Docker, CI/CD. Has a strong opinion on their IDE/editor of choice Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential.Knowledge of MLOps is not essential, but some awareness of this emerging space is more »

the 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 more »

Hands-on experience with Azure cloud services, including Azure Machine Learning, Azure Databricks, and Azure Synapse Analytics. Knowledge of machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. Experience with version control systems such as Git. Excellent problem-solving and analytical skills. Strong communication and teamwork skills. Active more »

related field, or a Bachelor's degree with relevant experience. Proven experience in machine learning model development and deployment, particularly with deep learning frameworks (Tensorflow, PyTorch, etc.). Strong understanding of speech recognition, natural language processing (NLP), and their applications in facial animation. Experience working with audio data processing more »

solutions within the insurance domain , Hands-on experience across predictive modelling, natural language processing, computer vision, and reinforcement learning. Proficiency in ML 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 more »

developing and testing API functionality, JavaScript, C++ and developing for scalability and systems architecture is required. Experience in networking, data management, machine learning, Pytorch, Tensorflow, Keras, and/or Cuda is desirable.Systems Integration Specialist- job responsibilities:Apply existing knowledge and experience of systems integration to the process of integrating more »

Code-Style Guidelines, Continuous Development and Version Control System in a product-oriented professional working environment. Expert coding in Python and C++. Experience using TensorFlow, SciPy and numerical software. Experience with machine learning and signal processing. Knowledge using AWS and/or Google Cloud. ‍ Desirables Experience coding in Cuda. 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 »

Vision models, particularly in the context of SLAM.Demonstrate proficiency in analyzing 3D Video and performing 3D reconstruction.Technical expertise: Python, Deep Learning frameworks (PyTorch or TensorFlow), AWS.SALARY AND BENEFITSCompetitive salary range: 65,000-90,000.Equity ownership in the company.Comprehensive benefits package.HOW TO APPLYPlease register your interest for this role by more »

experience developing and deploying machine learning models in a production environment - ideally in a start-up or scale-up. - Machine learning libraries and frameworks (TensorFlow, PyTorch, scikit-learn). - Python - Big data processing tools (e.g., Spark). The role offers a salary range of between £70-100K depending more »

Skills: Individuals in this role are expected to be accomplished in computational biology or machine learning. Experience using a deep learning frameworks like PyTorch, Tensorflow and/or Jax. Experience with any of the following biological topics would be a plus; Cryo-EM/ET data analysis: denoising, filtering more »

within a multi-strategy hedge fund environment. Strong programming skills in Python, R, or C++, with a focus on Machine Learning libraries such as TensorFlow or scikit-learn. Demonstrated success in developing and trading medium frequency statistical arbitrage strategies, with examples of applying Machine Learning techniques for predictive analytics. more »

GPUs. Understanding of NPU (neural processing unit) hardware and software. Strong knowledge of CNN and Transformer Architecture. Experience with ML frameworks like Pytorch/Tensorflow and programming languages C++ and Python. Desired Experience Industry experience at NPU, GPU, semiconductor manufacturers. What’s on offer Competitive Salary (£120k) Hybrid working more »

superior software solutions. Skills Required: In depth experience designing & building backend applications in Python. Familiarity with Big Data and Machine Learning technologies (NumPy, PyTorch, TensorFlow, Spark). Experience developing in a highly Agile/Scrum environment. Familiarity with CICD, containerisation, deployment technologies & cloud platforms (Jenkins, Kubernetes, Docker, AWS). more »

technologies, balancing the internal needs of Arm with those of the community. Experience building or using industry standard programmer's interfaces. Expert understanding of Tensorflow, PyTorch, Apache TVM, or comparable inference frameworks. Expert understanding of AI training, quantization and visualization tools. Proven experiences with LINUX. Comfortable presenting technical topics more »

top scientists, engineers, and designers in the company. Machine Learning Engineer - Ideal skillset would include: Top Academics in a relevant field Strong knowledge of TensorFlow, PyTorch, Keras and Scikit-Learn Ideally 1+ year professional experience as a Machine Learning Engineer Research minded and experimental approach to problem solving This more »

and implementing high-performance Python-based solutions to support our multi-strategy trading platform, leveraging cutting-edge libraries and frameworks such as NumPy, pandas, TensorFlow, and PyTorch. Collaborating closely with quantitative analysts and traders to develop and deploy sophisticated algorithmic trading strategies, utilizing advanced mathematical models and machine learning … understanding of its inner workings, including memory management, concurrency, and performance optimization. Proficiency in data science and machine learning libraries such as scikit-learn, TensorFlow, and PyTorch, with hands-on experience in developing and deploying machine learning models in production environments. Familiarity with financial markets and trading concepts, including more »