optimisation * Experience developing & deploying productionised Machine Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable) * Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated More ❯
hands-on orchestration Proficiency or experiment tracking, model management, and reproducibility Solid understanding of LLM architectures, fine-tuning, and inference optimizations Fluent in Python and model frameworks (PyTorch/TensorFlow, HuggingFace Transformers) Strong DevOps mindset; adept at CI/CD, infrastructure-as-code, and version control systems Job Title: Ai Engineer Location: London, UK Job Type: Contract Trading as More ❯
3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on GCP . Deep understanding of statistics, machine learning algorithms, and data modelling. Strong analytical mindset with a knack More ❯
3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on GCP . Deep understanding of statistics, machine learning algorithms, and data modelling. Strong analytical mindset with a knack More ❯
MLOps, Deep experience with Azure services, especially Azure Machine Learning, Azure Kubernetes Service (AKS), Azure Data Lake, and Azure Synapse, Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn, Strong understanding of MLOps concepts, including continuous integration/continuous, deployment (CI/CD) for ML, model versioning, monitoring, and retraining, Proficiency with Scripting and More ❯
and Data Science ? Experience as a trainer, instructor, or consultant in a technical field ? Strong communication and presentation skills for diverse learners ? Familiarity with AI tools such as Python, TensorFlow, PyTorch, Generative AI models (ChatGPT, LLMs) is desirable What's On Offer? ? Competitive daily rate: £400 - £500 p/d ? Flexible schedule with remote delivery options ? Opportunity to work More ❯
have a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Robert Half
have a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker More ❯
help shape AI risk frameworks. Required Skills & Experience 10+ years of professional experience, including demonstrable AI/ML expertise. Hands-on knowledge of LLMs, deep learning frameworks (eg, PyTorch, TensorFlow). Advanced Python skills; SQL a plus. Experience articulating risks in business terms and advising on mitigation. Excellent stakeholder communication skills, up to C-level. Strong analytical and reporting More ❯
Hands-on experience building and deploying NLP/LLM solutions, including summarisation, entity extraction, and topic modelling Strong Python skills with libraries such as HuggingFace Transformers, spaCy, PyTorch/TensorFlow, or RAG frameworks Experience with knowledge graphs, GNNs, or graph-enabled retrieval Proven ability to optimise ML systems for air-gapped, low-compute, or edge environments Understanding of evaluation More ❯
