1 to 25 of 44 PyTorch Jobs in Yorkshire

on Linux, Go, or similar. Utilise Advanced Technical Stack: Leverage our technical stack, including Python, SQL, PostgreSQL, BigQuery, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Pytorch, to develop robust and scalable AI/ML solutions. Strong foundation in data structures, algorithms, and problem-solving, with a clear focus on efficiency and optimisation. Experience with architecting and More ❯

monitoring (e.g. Kubeflow) Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) Working knowledge of object-oriented programming and unit testing in Python Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning) Working … right to close roles early when the particular role and/or location has had sufficient applications. Nice-to-have skills Python SQL Numpy Pandas PySpark YAML Terraform TensorFlow PyTorch Keras Scikit-learn Unit Testing Unix Scripting Docker Kubernetes AWS S3 DynamoDB Hull, England Work experience Machine Learning DevOps Languages English Seniority level Seniority level Mid-Senior level Employment type More ❯

written reports and presentations. This role is for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/ More ❯

Python, SQL, Unix-based systems, git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. Master's degree or PhD More ❯

and advanced AI/ML engineers and data scientists across various industries. Provide hands-on coding sessions and mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Incorporate cloud-based tools and services (AWS, GCP, Azure) into training to simulate modern ML environments (training on cloud tools can be provided). Update training materials to reflect More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

and model development. Expertise in SQL and statistical programming languages (e.g., Python, R), coupled with a deep understanding of data modelling principles. Mastery of machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and their application in complex problem domains. Extensive experience with MLOps principles and tools for model deployment, monitoring, versioning, and lifecycle management. Proven experience with analytics and visualisation More ❯

and model development • Expertise in SQL and statistical programming languages (e.g., Python, R), coupled with a deep understanding of data modelling principles • Mastery of machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and their application in complex problem domains • Extensive experience with MLOps principles and tools for model deployment, monitoring, versioning, and lifecycle management • Proven experience with analytics and visualisation More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the ability to More ❯

in designing, implementing, and optimizing computer algorithms for mission-critical systems. Proficiency in creating computer programs, including integration with larger software systems. Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and algorithm development tools. Experience with rapid-response R&D, including prototyping and experimental evaluation in dynamic environments. Strong problem-solving skills and the ability to bridge algorithm More ❯

they address specific business challenges. Coding & Implementation: Write, optimize, and implement AI code for model development, integrating generative AI models into scalable production environments. Use tools such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake to build and deploy AI solutions. Collaborate with other engineers on coding best practices, version control, and continuous integration/continuous delivery (CI More ❯

they address specific business challenges. Coding & Implementation: Write, optimize, and implement AI code for model development, integrating generative AI models into scalable production environments. Use tools such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake to build and deploy AI solutions. Collaborate with other engineers on coding best practices, version control, and continuous integration/continuous delivery (CI More ❯

they address specific business challenges. Coding & Implementation: Write, optimize, and implement AI code for model development, integrating generative AI models into scalable production environments. Use tools such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake to build and deploy AI solutions. Collaborate with other engineers on coding best practices, version control, and continuous integration/continuous delivery (CI More ❯