1 to 25 of 116 PyTorch Jobs in the North West

2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯

2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯

2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯

2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯

2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯

2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯

2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯

related field. 3+ years of 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 Platform. Ability to work with More ❯

Applied Maths, Computational Linguistics, or related fields (MSc/PhD preferred). Experience with computational linguistics is highly desirable. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, Scikit-learn. Experience deploying AI solutions using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD, and model performance monitoring. Background in behavioural biometrics, human-computer More ❯

. Any candidates with exposure 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 ML, and model performance monitoring. More ❯

. Any candidates with exposure 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 ML, and model performance monitoring. More ❯

Understanding of the mathematics of CNNs and GANs essential, or other advanced deep learning techniques. Proven experience in developing and deploying deep learning models using frameworks such as TensorFlow, PyTorch, Keras, or similar. Strong proficiency in programming in Python. Excellent problem-solving skills and the ability to work independently as well as in a team. Strong communication skills with the More ❯

MSc/PhD preferred). Exposure to computational linguistics is highly desirable, from both academic research and commercial perspectives. 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, or Azure. Hands-on experience with MLOps, CI/CD for ML, and model performance monitoring. More ❯

Press Tab to Move to Skip to Content Link Select how often (in days) to receive an alert: Lead Machine Learning Engineer, Associate Director 1 Requisition ID: 47862 Business Unit: Fitch Group Category: Information Technology Location: Manchester, GB Date Posted More ❯

to ensure smooth deployment of scalable solutions. Work closely with data scientists to deploy machine learning models into production environments. Optimise model inference performance (leveraging frameworks like TensorFlow or PyTorch for model serving) and implement monitoring to track model performance, accuracy, and reliability post-deployment. Keep up-to-date with the latest developments in Python, AI/ML technologies, and …/Machine Learning is a plus. Must have 8 years’ experience working as a Software Engineer on large software applications Proficient in many of the following technologies – Python, REST, PyTorch, TensorFlow, Docker, FastAPI, Selenium, React, TypeScript, Redux, GraphQL, Kafka, Apache Spark. Experience working with one or more of the following database systems – DynamoDB, DocumentDB, MongoDB Demonstrated expertise in unit testing … to ensure smooth deployment of scalable solutions. Work closely with data scientists to deploy machine learning models into production environments. Optimise model inference performance (leveraging frameworks like TensorFlow or PyTorch for model serving) and implement monitoring to track model performance, accuracy, and reliability post-deployment. Keep up-to-date with the latest developments in Python, AI/ML technologies, and More ❯

to ensure smooth deployment of scalable solutions. Work closely with data scientists to deploy machine learning models into production environments. Optimise model inference performance (leveraging frameworks like TensorFlow or PyTorch for model serving) and implement monitoring to track model performance, accuracy, and reliability post-deployment. Keep up-to-date with the latest developments in Python, AI/ML technologies, and …/Machine Learning is a plus. Must have 8 years’ experience working as a Software Engineer on large software applications Proficient in many of the following technologies – Python, REST, PyTorch, TensorFlow, Docker, FastAPI, Selenium, React, TypeScript, Redux, GraphQL, Kafka, Apache Spark. Experience working with one or more of the following database systems – DynamoDB, DocumentDB, MongoDB Demonstrated expertise in unit testing 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 ❯

Proven ability to lead technical direction across projects or domains Expertise in model validation, explainability, governance and ethical AI principles Advanced proficiency in Python (e.g. Scikit-learn, TensorFlow/PyTorch) and SQL, plus familiarity with ML engineering and MLOps practices Nice to have: Experience in setting or influencing data science strategy in a growing organisation Familiarity with AWS SageMaker and 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 ❯

prototype AI/ML models 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 requirements, identify opportunities, and communicate More ❯

similar roles. Proven track record in designing and deploying scalable machine learning systems in production. Strong programming skills in Python and experience with ML frameworks and tools (e.g., TensorFlow, PyTorch, MLFlow, Kubeflow, Jupyter, Azure ML Studio, Amazon Sagemaker, Apache Spark, Apache Flink). Expertise in containerization (e.g., Docker, Kubernetes) and automation (e.g., Jenkins, GitLab CI). Excellent problem-solving skills More ❯

tooling: Git, Unix/Linux, 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 essential, but some awareness of More ❯

Azure, (Azure ML, Azure Stream 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 and organisation skills Ability to … Azure, (Azure ML, Azure Stream 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 Ability to diagnose and troubleshoot More ❯

governance standards. Data Scientist experience we’re looking for – Proven experience in a commercial Data Science role. Strong proficiency in Python (including libraries like pandas, scikit-learn, TensorFlow or PyTorch). Solid understanding of machine learning algorithms, data modelling, and statistical analysis. Hands-on experience working with large datasets and data wrangling techniques. Familiarity with cloud-based environments, particularly AWS. More ❯

governance standards. Data Scientist experience we’re looking for – Proven experience in a commercial Data Science role. Strong proficiency in Python (including libraries like pandas, scikit-learn, TensorFlow or PyTorch). Solid understanding of machine learning algorithms, data modelling, and statistical analysis. Hands-on experience working with large datasets and data wrangling techniques. Familiarity with cloud-based environments, particularly AWS. More ❯