City of London, London, United Kingdom Hybrid / WFH Options
Experis UK
PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options
Experis UK
PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. More ❯
NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/data platforms (Databricks, Tecton, etc.). Strong experience with cloud platforms (AWS, GCP, or Azure), Docker, and Kubernetes. Solid coding practices, including Git, automated testing, and CI More ❯
tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯
london (city of london), south east england, united kingdom
Inferity AI
tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯
Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in More ❯
london (city of london), south east england, united kingdom
Luxoft
Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in More ❯
including training, evaluation, and optimisation. Strong grounding in mathematics, statistics, and data analysis. Experience working in Agile environments. Familiarity with technologies such as AWS, GCP, Kubernetes, Ray Serve, and Kubeflow is desirable. ---------------------------------------- Professional Values Growth: Demonstrates curiosity, adaptability, and continuous learning. Accountability: Takes ownership and delivers to a high standard. Innovation: Embraces experimentation and emerging technologies to drive progress. Collaboration More ❯
