clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication skills. Preferred Knowledge More ❯
and architectures such as ReAct for building more effective autonomous agents for complex property management workflows and decision-making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their AI/ML offerings Preferably More ❯
Optimization: Demonstrated ability to fine-tune and optimize LLMs for quality, latency, sustainability and cost-effective performance. Programming and NLP Tooling: Advanced Python proficiency and expertise with frameworks like PyTorch, TensorFlow, Hugging Face, or LangChain. MLOps and Deployment: Experience with containerization tools (Docker, Kubernetes) and workflow management tools (Azure ML Studio, MLFlow). Cloud and AI Infrastructure: Hands-on experience More ❯
You have deep experience with the AWS ecosystem and services relevant to ML, such as SageMaker, EC2, S3, IAM, and VPC. You are familiar with deep-learning frameworks like PyTorch or JAX, and libraries from the AI ecosystem like Hugging Face Transformers. You have worked with the lifecycle of AI models, including deployment, hosting, and optimization for low-latency inference. More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Method Resourcing
familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed More ❯
their strategic value Qualifications Experience Extensive experience in data science, machine learning, or advanced analytics, ideally in a technical leadership role Proven expertise in Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and experience across NLP, computer vision, and LLMs Strong statistical foundation, including A/B testing, causal inference, and experimental design Proficiency in SQL and working with More ❯
natural language processing or reinforcement learning Proven track record applying AI and ML to solve complex business problems, ideally in marketing, advertising or e-commerce Strong proficiency in Python (PyTorch, TensorFlow, scikit-learn), SQL and cloud ML orchestration environments such as AWS, Databricks or Flyte Experience with search marketing, ad auctions, bidding optimisation or customer segmentation is a plus Skilled More ❯
expertise to influence decision-making and enhance product functionality Key Skills Proficiency in Python and/or R for developing machine learning models. Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. Knowledge of version More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
NonStop Consulting Ltd
production that have tangible, high-profile impact. Essential experience: Strong background in Computer Vision and image/video processingHands-on experience with OpenCV pipelines Proficiency with deep learning frameworks (PyTorch, TensorFlow, Keras)Knowledge of CNN architectures and training dynamicsProven experience deploying and optimizing models for real-time applicationsStrong data science and metrics literacy Nice to have: PhD or Master's More ❯
that have tangible, high-profile impact. Essential experience: Strong background in Computer Vision and image/video processing Hands-on experience with OpenCV pipelines Proficiency with deep learning frameworks (PyTorch, TensorFlow, Keras) Knowledge of CNN architectures and training dynamics Proven experience deploying and optimizing models for real-time applications Strong data science and metrics literacy Nice to have: PhD or More ❯
for Active SC clearance(minimum 5 years UK residency required). Strong software engineering skills, with proficiency in Python. Experience across the ML lifecycle, including deploying models built in PyTorch, TensorFlow, or Scikit-learn. Hands-on cloud experience with AWS, Azure, or GCP. Knowledge of Docker and Kubernetes, with practical containerisation experience. Understanding of probability, statistics, and ML techniques. Strong More ❯
. Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions, including Snowflake. Understanding of personalization More ❯
Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯
Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯
directly impact business outcomes. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to deliver robust AI solutions. Key Skills Proficiency in Python, TensorFlow, or PyTorch Experience with machine learning algorithms and frameworks Strong understanding of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML More ❯
Cheltenham, Gloucestershire, South West, United Kingdom
Anson Mccade
to junior engineers, championing best practice and technical standards. What We're Looking For Strong experience across the ML lifecycle, including deploying models built in frameworks such as TensorFlow, PyTorch or Scikit-learn. Solid software engineering skills, with strong Python programming experience. Hands-on knowledge of cloud platforms (AWS, Azure, or GCP), containers, Docker, and Kubernetes. Understanding of probability, statistics More ❯
Cheltenham, Gloucestershire, South West, United Kingdom Hybrid / WFH Options
Anson Mccade
to junior engineers, championing best practice and technical standards. What We're Looking For Strong experience across the ML lifecycle, including deploying models built in frameworks such as TensorFlow, PyTorch or Scikit-learn. Solid software engineering skills, with strong Python programming experience. Hands-on knowledge of cloud platforms (AWS, Azure, or GCP), containers, Docker, and Kubernetes. Understanding of probability, statistics More ❯
Birmingham, West Midlands, United Kingdom Hybrid / WFH Options
Anson Mccade
programming background; must be able to quickly become fluent in Python . Proficiency with key data science libraries (NumPy, Pandas, Scikit-Learn) and experience with deep learning frameworks (TensorFlow, PyTorch, or Caffe). Strong mathematical and statistical skills. Broad knowledge of core data science techniques, such as: Supervised/unsupervised machine learning Cross-validation and Bayesian inference Time-series analysis More ❯
BT9, Windsor, City of Belfast, County Antrim, United Kingdom Hybrid / WFH Options
Exposed Solutions
and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯
managing ML in production. What we're looking for Active SC Clearance Strong software engineering background with proficiency in Python. Experience deploying ML models built with frameworks such as PyTorch, TensorFlow, or Scikit-learn. Knowledge of probability, statistics, and common ML techniques. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP). Proficiency with containers More ❯
Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big More ❯
programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning More ❯
engineering, or computer science - Experience communicating across technical and non-technical audiences - Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet - Fluency in written and spoken English Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions More ❯
