1 to 25 of 33 Amazon SageMaker Jobs in the UK

validation, bias/fairness testing, explainable AI (XAI) techniques, and performance monitoring. Qualifications & Experience (Preferred) Publications in recognized AI/ML journals or conferences. Experience with cloud platforms (AWS SageMaker, Google Vertex AI, Azure ML). Knowledge of graph databases and network analysis techniques. Experience with real-time model inference and API development (e.g., FastAPI, Flask). Personal Attributes More ❯

a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience with More ❯

a DataOps or DevOps approach. Demonstrate how to automate and manage data systems so they run smoothly and can grow easily. Experience with tools like AWS (S3, Glue, Redshift, SageMaker) or other cloud platforms. Familiarity with Docker, Terraform, GitHub Actions, and Vault for managing secrets. Experience in coding SQL, Python, Spark, or Scala to work with data. Experience with More ❯

facing technical role such as Solutions Engineer, Sales Engineer, Developer Advocate, or Technical Consultant. 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 More ❯

gates. AI/ML Infrastructure Security: Harden and secure the underlying cloud infrastructure for AI/ML workloads, including GPU clusters, container orchestration (Kubernetes), and managed services (e.g., AWS SageMaker, Azure ML). Security by Design: Embed security controls into every stage of the ML lifecycle (data ingestion, feature store, model training, deployment, monitoring). Implement secrets management, network 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 ❯

Collaborate closely with data scientists and software engineers to productionize prototypes into scalable, maintainable solutions. Essential Skills & Experienc: • Hands-on experience with ML Ops tools such as MLflow, Kubeflow, Amazon SageMaker, Vertex AI, orequivalent platforms. • Deep understanding of cloud infrastructure services (AWS, Azure, GCP). • Strong experience with CI/CD practices and containerization tools (Docker, Kubernetes). More ❯

on cutting-edge machine learning and data engineering projects, leveraging the latest cloud technologies and MLOps practices. Required/Primary Skills: AWS Data Engineering ML Engineering ML-Ops ECS, Sagemaker Gitlab Jenkins CI/CD AI Lifecycle Experience in front-end development (HTML, Stream-lit, Flask Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

for a Data Engineer for FS domain with Machine learning and MLOps background and proficiency in Python. YOUR PROFILE Primary Skill: AWS Data Engineering, ML Engineering, ML-Ops, ECS, Sagemaker, Gitlab, Jenkins, CI/CD, AI Lifecycle, Experience in front-end development (HTML, Stream-lit, Flask.) Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

for a Data Engineer for FS domain with Machine learning and MLOps background and proficiency in Python. YOUR PROFILE Primary Skill: AWS Data Engineering, ML Engineering, ML-Ops, ECS, Sagemaker, Gitlab, Jenkins, CI/CD, AI Lifecycle, Experience in front-end development (HTML, Stream-lit, Flask.) Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

for a Data Engineer for FS domain with Machine learning and MLOps background and proficiency in Python. YOUR PROFILE Primary Skill: AWS Data Engineering, ML Engineering, ML-Ops, ECS, Sagemaker, Gitlab, Jenkins, CI/CD, AI Lifecycle, Experience in front-end development (HTML, Stream-lit, Flask.) Familiarity with model deployment and monitoring in cloud environments (AWS). Understanding of More ❯

conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML: Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms (e.g., Google Vertex AI, AWS Sagemaker). Hands-on work with Generative AI, Large Language Models (LLMs), agent-based frameworks, and prompt engineering. LI-YUnleash Your PotentialWhen you join Salesforce, you'll be limitless in More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills 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 ❯

with the organisation's existing team to support the delivery of one of the organisation's key strategic initiatives. Experience required: AWS Data/ML Engineering & ML Ops (ECS, Sagemaker) CI/CD pipelines (GitLab, Jenkins) Python, PySpark & Big Data ecosystems AI/ML lifecycle, deployment & monitoring MLOps tooling (MLflow, Airflow, Docker, Kubernetes) Front-end exposure (HTML, Flask, Streamlit 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 ❯

and ML engineers to reduce time-to-production for experiments and prototypes. Design and optimize data wrangling and transformation workflows using Python. Leverage AWS cloud services (EC2, S3, Lambda, SageMaker, RDS, DynamoDB, Redshift, etc.) to build robust, scalable, and cost-effective solutions. Apply AIOps practices to enhance monitoring, automation, and resilience of ML systems. Implement best practices in data … software engineering principles. Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows. Expertise in AWS services, including databases (RDS, DynamoDB, Redshift) and machine learning/AI (SageMaker, AI/ML frameworks). Hands-on experience with ML pipeline orchestration, CI/CD, and deployment automation. Deep understanding of ML Ops practices, including monitoring, scaling, and retraining More ❯

LangGraph, LlamaIndex Experience with Hugging Face and LoRA/QLoRA for fine-tuning Experience with RAG & Vector DBs eg. FAISS, Weaviate, Pinecone Any experience of MLOps with MLFlow, AWS (SageMaker), CI/CD (GitHub Actions) or similar would be a benefit to an application The employer is well known not only for the forward-thinking approach they have to 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 ❯

Senior Delivery Consultant - AI/ML, ASEAN Professional Services Job ID: Amazon Web Services Philippines Inc. The Amazon Web Services Professional Services (AWS ProServe) ASEAN organization is looking for a senior experienced and motivated business-oriented AI/ML practitioner who possess a unique balance of business knowledge and Technology depth in Machine Learning with deliver implementation experience … the use of machine learning - Provide technical leadership and excellence on customer engagements to ensure alignment on scope, deliverables, timeline and customer expected outcomes About the team Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage 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 successful startups to Global 500 companies More ❯

SENIOR DATA ENGINEER PERMANENT CITY OF LONDON £90,000 - £100,000 HYBRID work available - City of London office/Home As a key member of this team, you will play a pivotal role in designing and implementing data warehousing solutions More ❯

SENIOR DATA ENGINEER PERMANENT CITY OF LONDON £90,000 - £100,000 HYBRID work available - City of London office/Home As a key member of this team, you will play a pivotal role in designing and implementing data warehousing solutions More ❯

SENIOR DATA ENGINEER PERMANENT CITY OF LONDON £90,000 - £100,000 HYBRID work available - City of London office/Home As a key member of this team, you will play a pivotal role in designing and implementing data warehousing solutions More ❯