1 to 25 of 28 TensorFlow Jobs in Scotland

guardrails, and AI quality assessment.Good foundation in statistics, probability, optimization, experimentation, and applied machine learning.Advanced proficiency in Python and modern AI frameworks, including PyTorch, TensorFlow, Scikit-Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems.Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands ...

e.g., Python, R), with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development ...

e.g., Python, R), with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. ...

programming languages used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation ...

programming languages used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation ...

Generative AI solutions; evidence of real-world impact highly desirable.Expert-level proficiency in Python, and modern AI/ML frameworks, including PyTorch, TensorFlow, and specialised Generative AI libraries (LangChain, LangGraph or related open-source toolkits strongly preferred. Background in Traditional ML/AI is preferred.Deep understanding of LLMs, prompt ...

Generative AI solutions; evidence of real-world impact highly desirable.Expert-level proficiency in Python, and modern AI/ML frameworks, including PyTorch, TensorFlow, and specialised Generative AI libraries (LangChain, LangGraph or related open-source toolkits strongly preferred. Background in Traditional ML/AI is preferred.Deep understanding of LLMs, prompt ...

production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy, spaCy, PyTorch or TensorFlow). Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real-world business applications. Proven ...

observability, debugging, and testing approaches for AI/ML systems, including non-deterministic and agentic applications. Machine learning and optimization frameworks such as PyTorch, TensorFlow, or JAX. Distributed systems, cloud infrastructure, model serving, orchestration, data pipelines, and API design. Performance optimization across latency, throughput, compute utilization, reliability, scalability ...

modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

datasets to generate actionable insights that inform business and product decisions Desirable: Hands-on coding and prototyping experience in AI/ML development (Python, TensorFlow, PyTorch) Experience with proof-of-concept development and technical validation of new AI technologies Background in data science or machine learning engineering with ...

Need... Confirmed experience in leading data science projects in cybersecurity, fraud, or behavioural analytics. Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch), and cloud platforms (preferably GCP). Deep Learning Theory & Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures. Experience with ...

need...Confirmed experience in leading data science projects in cybersecurity, fraud, or behavioural analytics. Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch), and cloud platforms (preferably GCP). Deep Learning Theory & Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures. Experience with LLMs ...

observability, debugging, and testing approaches for AI/ML systems, including non-deterministic and agentic applications. Machine learning and optimization frameworks such as PyTorch, TensorFlow, or JAX. Distributed systems, cloud infrastructure, model serving, orchestration, data pipelines, and API design. Performance optimization across latency, throughput, compute utilization, reliability, scalability ...

Experience with retrieval systems for agents: retrieval-augmented generation, embedding models, vector databases, and long-term memory. Experience with machine learning libraries (e.g. PyTorch, Tensorflow), cloud platforms (AWS, Azure, GCP), and the analysis of financial or economic data. Experience helping define technical standards, best practices, or ways of working ...

experimentation, observability, debugging, and testing approaches for AI/ML systems, including non-deterministic and agentic applications. Machine learning and optimization frameworks such asPyTorch, TensorFlow, or JAX. Distributed systems, cloud infrastructure, model serving, orchestration, data pipelines, and API design. Performance optimization across latency, throughput, computeutilization, reliability, scalability, and cost. ...

related discipline, or equivalent industry experience. Strong proficiency in relevant programming languages (Python – essential; C++ – preferred; SQL – exposure), tools and technologies (Pytorch or Tensorflow – essential; Opencv, Scipy, Pandas, or equivalent libraries for image processing and data science - essential; MS Azure Synapse – exposure) used in the development of machine learning ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment. Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML). Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies. ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment.Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML).Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies.Experience operating ...

following technical skills:Industry experience working on Agile projects across the full software life cycle.Proficiency in machine learning frameworks such as PyTorch and TensorFlow, as well as tools for model integration.A strong foundation in AI/ML, including transformer architectures, tokenisation, embeddings, and fine-tuning large language models (LLMs ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment. Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML). Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies. ...

/throughput improvements Preferred: Experience with LLVM/MLIR development AI Model Profiling & Framework Optimization: Profile end-to-end inference workflows on frameworks like TensorFlow, PyTorch, ONNX, and llama.cpp to identify hotspots and bottlenecks Propose and implement optimization strategies (e.g., kernel tuning, graph-level optimizations) Preferred: Experience optimizing models ...