1 to 25 of 105 TensorFlow Jobs in the North West

engineering. 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. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 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. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 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. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 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. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 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. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 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. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 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. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

considered. 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 More ❯

a 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 More ❯

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 ❯

/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 ❯

cloud services) 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/… 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 … cloud services) 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/ More ❯

cloud services) 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/… 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 ❯

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 ❯

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/AWS More ❯

reinforcement learning) 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 More ❯

security and 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 More ❯

and 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 More ❯

security and 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 More ❯

security and 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 More ❯

security and 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 More ❯

core software 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 More ❯

or 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 More ❯