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 ❯
City of London, London, United Kingdom Hybrid / WFH Options
Experis UK
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, south east england, united kingdom Hybrid / WFH Options
Experis UK
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
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 ❯
slough, south east england, united kingdom Hybrid / WFH Options
Experis UK
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 ❯
ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems. Strong knowledge of APIs, microservices architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end-to-end More ❯
to communicate technical solutions clearly to non-technical stakeholders Technical skills (a big plus): Knowledge of deep learning frameworks (PyTorch, TensorFlow), transformers, or LLMs Familiarity with MLOps tools (MLflow, SageMaker, Airflow, etc.) Experience with streaming data (Kafka, Kinesis) and distributed computing (Spark, Dask) Skills in data visualization apps (Streamlit, Dash) and dashboarding (Tableau, Looker) Domain experience in forecasting, optimisation More ❯
to communicate technical solutions clearly to non-technical stakeholders Technical skills (a big plus): Knowledge of deep learning frameworks (PyTorch, TensorFlow), transformers, or LLMs Familiarity with MLOps tools (MLflow, SageMaker, Airflow, etc.) Experience with streaming data (Kafka, Kinesis) and distributed computing (Spark, Dask) Skills in data visualization apps (Streamlit, Dash) and dashboarding (Tableau, Looker) Domain experience in forecasting, optimisation More ❯
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 ❯
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 ❯
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 ❯
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
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 ❯
South East London, London, United Kingdom Hybrid / WFH Options
Stepstone UK
Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semantic search, or event-driven systems like Kafka Additional More ❯
training techniques including fine-tuning, RLHF, parameter-efficient methods (LoRA/QLoRA), or custom post-training workflows MLOps experience : Knowledge and familiarity with MLOps frameworks and tools such as Sagemaker, Kedro, MLflow or Weights and Biases Energy Domain Knowledge: Background in power systems, energy dispatch optimisation, grid modelling, or other energy sector applications where AI/ML drives operational … proficiency with hands-on experience in AI/ML frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker, Kedro and More ❯
/ML Skills: Deep knowledge of at least one leading cloud platform (AWS, Azure, or Google Cloud Platform). Experience with cloud-native AI/ML services (e.g., AWS SageMaker, Azure ML, Google AI Platform), enabling secure integration and operationalization of models. Infrastructure as Code (Terraform, CloudFormation, ARM) and AI-powered IaC generation tools. Cloud security (IAM, encryption, compliance More ❯
services. Hands on experience with DevOps and engineering tools (GitLab, GitHub, Azure DevOps, Docker, Kubernetes). Proficiency with AI/ML and MLOps platforms (Databricks, Google Cloud Vertex AI, SageMaker). Familiarity with generative AI technologies and frameworks (OpenAI, Google Gemini, Hugging Face Transformers). Demonstrated success in developing and executing product strategies. Ability to lead and inspire cross More ❯
london, south east england, united kingdom Hybrid / WFH Options
Compare the Market
Looking For Must Have Practical experience deploying ML models into production environments Strong Python development skills and understanding of ML model structures Familiarity with tools such as MLflow, Airflow, SageMaker, or Vertex AI Understanding of CI/CD concepts and basic infrastructure automation Ability to write well-tested, maintainable, and modular code Strong collaboration skills and a growth mindset More ❯
HIPAA) Excellent communication, client engagement, and workshop facilitation skills Proven ability to work in matrix environments across global teams Desired skills Exposure to AI platforms like Azure AI, AWS SageMaker, Google Vertex AI Knowledge of PoC packaging and offer development for enterprise clients Experience Experience working with AI CoEs or global delivery teams Benefits Collaborative working environment - we stand More ❯
integration. Familiarity with CI/CD pipelines and modern DevOps workflows. Understanding of authentication, authorization, and web security best practices. Nice-to-haves: Experience deploying ML models using AWS Sagemaker, Hugging Face, or Replicate . Familiarity with WebGL, THREE.js , or other 3D graphics frameworks. Interest in AI, generative models, and spatial computing . More ❯
years experience AWS cloud and AWS services such as Redshift, DMS, RDS, Glue, S3, Athena, Lambda Experience in designing and managing a data warehouse Experience with AWS Bedrock, Sagemaker and PowerBI desirable Strong capability with SQL in both MySQL and Postgresql flavours About You A self-starter looking to make a positive impact in a rapidly evolving environment Ability More ❯
technologies based on client delivery experience and research Qualifications We are looking for experience in the following skills and experience: AI/ML platform technologies and services such as Sagemaker/Vertex/Azure ML, OpenAI, Langchain, AutoML, OCR, STT, feature stores, vector DB AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG More ❯
Senior Machine Learning Engineer page is loaded Senior Machine Learning Engineer Apply locations London, UK time type Full time posted on Posted 5 Days Ago job requisition id R15074 Job Title Senior Machine Learning Engineer Job Description Here at UnderwriteMe More ❯
from strategic planning through to pre-production deployment and optimisation Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams Partner with customers to translate business challenges into measurable ML … candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most … software development life cycle (sdlc) and agile/iterative methodologies Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We More ❯
Job ID: Amazon Development Centre (Scotland) Limited Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people … of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly … the right time. You'll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the More ❯