17 of 17 Permanent PyTorch Jobs in the North West

experience in AI development. Strong understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experienced with cloud platforms such as Amazon Web Services, Azure, or Google Cloud More ❯

to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯

to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯

ML algorithms, ranging from classical techniques to deep learning methods. Proven experience in training, fine-tuning, and deploying neural network models using frameworks like PyTorch, with a focus on optimizing performance and scalability for real-world applications. Demonstrated ability to mentor and lead technical teams, influence technical strategy, and drive More ❯

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 More ❯

to address business challenges (e.g., process automation, predictive analytics, customer service optimisation) Develop and deploy machine learning models using modern tools (e.g., Python, TensorFlow, PyTorch, Scikit-learn) Collaborate with data engineers to prepare and manage training datasets Integrate AI solutions with existing applications and infrastructure Partner with stakeholders to understand More ❯

to address business challenges (e.g., process automation, predictive analytics, customer service optimisation) Develop and deploy machine learning models using modern tools (e.g., Python, TensorFlow, PyTorch, Scikit-learn) Collaborate with data engineers to prepare and manage training datasets Integrate AI solutions with existing applications and infrastructure Partner with stakeholders to understand More ❯

Docker. Plus, a strong opinion on your IDE/editor of choice is welcome ;) Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential. Excellent communication skills; both in customer-facing and internal team communication. Knowledge of MLOps is not More ❯

to-end solutions Implement testing, monitoring, and performance optimisation of ML systems Contribute to architectural discussions and promote engineering best practices Technical Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks More ❯

deploying machine learning models and algorithms in real-world applications. - Strong proficiency in Python programming and popular machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning concepts and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Strong communication and interpersonal More ❯

concept through to deployment, with the ability to communicate effectively to both technical and non-technical stakeholders. Proficiency with machine learning frameworks, such as PyTorch or TensorFlow. Strong expertise in deep learning algorithms, model architectures, and the AI development lifecycle. Hands-on experience with the latest technologies and models in More ❯

We’re Looking For: 2+ years in AI/ML engineering or backend software roles with ML components. Proficiency in Python and frameworks like PyTorch/TensorFlow, Scikit-learn. Experience deploying models with Docker, Kubernetes, or serverless architectures. Solid grasp of MLOps workflows, versioning, and cloud automation. Strong foundations in More ❯

with equivalent industry experience) Experience working with LLMs, speech technologies (ASR, TTS), or multimodal systems Strong programming skills in Python, with experience in using PyTorch Hands-on experience with training and fine-tuning ML models, including setting up experiments and evaluating results Ability to read, interpret, and implement techniques from More ❯

TorchServe). Experience with GPU scaling for large-scale machine learning models. Expertise in deploying complex machine learning pipelines in production environments. Proficiency with PyTorch and Hugging Face transformers. Experience with neural audio codecs (e.g., Encodec). Background in Text-to-Speech (TTS) development. Experience with advanced techniques such as More ❯

Familiarity with modern DevOps practices (CI/CD pipelines, Docker, etc) Nice to have but not essential: Exposure to ML frameworks like TensorFlow or PyTorch (not essential) Experience in e-commerce or retail tech environments This is a hybrid role 2 days a week in office, so candidates must be More ❯

with equivalent industry experience) Experience working with LLMs, speech technologies (ASR, TTS), or multimodal systems Strong programming skills in Python, with experience in using PyTorch Hands-on experience with training and fine-tuning ML models, including setting up experiments and evaluating results Ability to read, interpret, and implement techniques from More ❯

Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management … Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills More ❯