26 to 50 of 64 Amazon SageMaker Jobs in England

systems in production or a very strong software‐engineering background with clear motivation to grow into ML and MLOps. Additional Experience & Capabilities Using AWS SageMaker for training, deploying, and operating machine-learning workloads, or demonstrating equivalent experience on similar cloud ML platforms. Exposing machine-learning models via APIs (e.g. ...

documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands‐on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML). Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment for all of our employees ...

Bedrock Experience with Kubernetes, CI or CD, infrastructure as code, and automation tools Familiarity with AI or ML platforms such as Databricks, SageMaker, or MLflow Exposure to hybrid cloud architectures and large scale data processing ecosystems Knowledge of enterprise data platforms, observability, and cost management tooling Leadership Expectations ...

experience in using one of 3 major cloud technologies ( AWS, Azure or GCP ) in a production environment, as well as ML platforms ( e.g., AWS Sagemaker, Azure Machine Learning studio ) Be a ‘lifelong learner’ and can demonstrate a drive to always be learning and developing your skillsets and develop ...

understanding of model capabilities and limitations—not just using AI to generate code. Highly desirable: EdTech or Education experience Java Terraform Kubernetes LangChain, Bedrock, SageMaker or similar GenAI tooling OAuth/JWT This is an excellent opportunity to join a global organisation at the forefront of AI innovation, building ...

Technology Stack Backend: TypeScript, Node.js, C#, .NET Infrastructure: AWS (ECS, Lambda, SQS, DynamoDB), Terraform Architecture: Microservices, Event‐driven architecture Data & ML: Python, AWS SageMaker, S3, Redshift Why Join Alto? This role gives you genuine ownership of ML capability at a company that processes more housing transactions than anyone else ...

Swift on iOS. Data: SQL, Python, Snowflake, dbt, Airflow & Looker AI at Marshmallow: Sierra.ai for conversational AI, Python and LangChain for agentic AI solutions, Sagemaker and MLflow for Machine Learning, Cursor and Claude Code for developer productivity. What you'll be doing Drive commercial impact at every turn: Proactively ...

Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like Databricks, Snowflake, SageMaker, or Vertex. Agent lifecycle management, observability, and governance frameworks.Agentforce & Salesforce Platform Deep architectural understanding of how Data and AI are activated within Salesforce — including ...

Familiarity with cloud‐based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J-18808-Ljbffr ...

Preferred Qualifications, Capabilities & Skills Product management experience for AI/ML, MLOps, or data platforms. Familiarity with MLOps concepts and frameworks, such as MLflow, Amazon SageMaker, and feature stores. Familiarity with AI concepts, such as Retrieval‐Augmented Generation (RAG), agentic system architectures, evaluation of LLMs and agents … Model Context Protocol (MCP). Hands‐on experience with or solid understanding of Amazon Web Services (AWS). Understanding of cloud architecture and the software development lifecycle. Experience coaching and mentoring other product managers and setting a high bar for execution. Experience operating at scale in highly available, secure ...

production. Experience with AutoML frameworks. Strong understanding of regression, forecasting, and predictive analytics. Data engineering and pipeline development capability. AWS ML deployment experience (e.g. SageMaker, ECS, Lambda). Practical MLOps experience. Excellent stakeholder management and consulting skills. Experience mentoring data science teams. AWS-native ML tooling and cloud architecture ...

rich metadata, automated quality profiling, and governance guardrails. Consumers: Reduce friction from discovery to access — self‐service provisioning, entitlement workflows, one‐click integration with SageMaker, Databricks, and EMR. Network effects: Analyze usage trends to improve data quality, discovery and relevancy across persona groups. Collaborate with Engineering, Design & Data Science ...

organisation. What We Are Looking For MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms. ML Infrastructure Experience: Proven track record of working on ML research and production infrastructure. Infrastructure as Code: Knowledge of IaC tools such ...

ability to present complex information through clear and compelling data visualisations, ideally using Tableau Experience of cloud-based data science technologies, ideally including AWS SageMaker, AWS Bedrock and Snowflake , would be highly desirable A passion for continuous learning and staying up to date with emerging data science tools, technologies ...

expand from a GCP‐first environment to a hybrid AWS and GCP architecture. Define GPU compute strategy across Kubernetes, Vertex AI and SageMaker, balancing performance, scalability and cost efficiency. Drive the production adoption of Generative AI and LLM capabilities, establishing best practices for evaluation, deployment, experimentation and governance. Collaborate ...

content classification, synthetic panels, model validation). Experience with data platforms such as Databricks, snowflake or other cloud native solutions (GCP big query, AWS sagemaker). Solid understanding of agile practices. Any experience in SAFe is considered a plus. How we work Fifty5Blue’s core values are: Clarity, Independence ...

implementation. Required Skills & Experience Deep experience architecting and scaling enterprise-grade AI/ML systems . Proven expertise with cloud AI ecosystems (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong command of agent frameworks , vector databases , and LLM orchestration tools . Ability to lead multi-disciplinary teams ...

learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC). Experience developing LLM or Generative … agents and agentic workflows. Vector databases such as Pinecone, Weaviate, or pgvector. Feature stores including Feast or AWS Feature Store. Docker, Kubernetes, or Amazon ECS. Infrastructure as Code using Terraform or CloudFormation. Big data processing technologies such as Spark or Dask. Experience working within regulated or highly secure environments. ...

models into production, balancing quick wins with robust engineering. Focus areas include AI/OCR workflows, RAG systems, and deploying models on AWS with SageMaker/Bedrock. This hybrid role requires 1–2 days in Central London per week and right to work in the UK. #J-18808-Ljbffr ...

models influence real lending decisions and commercial outcomes Experience deploying and maintaining models within production environments Strong Python, SQL and AWS experience (particularly SageMaker and Lambda) Comfortable working in a fast-moving, hands-on environment with high ownership Excellent communication skills with both technical and business stakeholders What ...

strong expertise in SQL and Python being desirable. We're utilising the Data Science tools in the AWS Stack, so a good understanding of Sagemaker, Bedrock, and AWS Cloud Components would be highly desirable. Snowflake is our Central Data Platform, of which some experience would be desirable. Demonstrable experience ...

models including scorecards, behavioural, acquisition and fraud models Build predictive models using advanced statistical and machine learning techniques Deploy models into production using AWS SageMaker and collaborate with engineering teams Monitor model performance and ensure ongoing effectiveness across business and technical metrics Generate insights and present clear, actionable recommendations ...

vision to delivery, across a hybrid UK environment. You will leverage AWS analytics services to build secure, governed lakehouse and warehouse solutions, integrating with SageMaker and ensuring scalable, auditable data products while collaborating with cross-functional teams to implement CI/CD and governance practices. #J-18808-Ljbffr ...

environment evolves, but typical tools include: Python for experimentation, modelling, and evaluation Weights & Biases (or equivalent) for experiment tracking AWS , including services such as SageMaker and Bedrock Internally supported AI development platforms and tooling This role is not suited to candidates who are dogmatic about specific tools . Adaptability ...

provide technical leadership across the full lifecycle of machine learning systems while architecting production-grade ML solutions. You will work with AWS SageMaker, lead teams on MLOps strategies, and ensure systems adhere to governance standards. This is a hands-on, technical position ideal for those with deep expertise ...