19 of 19 Permanent Amazon SageMaker Jobs in the South East

large and complex datasets to solve high impact, customer facing product problems• Design, build, train, and deploy machine learning models using AWS services, with Amazon SageMaker as the core ML platform• Develop and productionise recommendation and personalisation systems used at scale• Own the full model lifecycle including experimentation … product or customer focused environment• Strong Python and SQL skills• Hands on, production experience using AWS for machine learning workloads• Strong experience with Amazon SageMaker for model training, deployment, and monitoring• Experience building and deploying machine learning models into live products• Solid understanding of applied machine learning techniques ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

large language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data ...

PyTorch Experience with containerization tools like Docker and orchestration tools like Airflow or Astronomer Familiarity with cloud platforms (AWS, Azure) and ML services (e.g., SageMaker, Vertex AI) Experience with CI/CD pipelines and automation tools such as GitHub Actions Understanding of monitoring and logging tools (e.g., NewRelic, Grafana ...

detail, and ability to work independently and collaboratively Highly desirable AWS certifications (e.g., DevOps Engineer, Solutions Architect) Experience with AWS generative AI services (Bedrock, SageMaker) Open-source contributions demonstrating engineering best practices Benefits Work on cutting-edge generative AI projects Join a talented, innovative team Competitive salary and benefits ...

infrastructure, and cloud-native tooling. Tech Stack Programming: Python (Java familiarity is a plus). AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and more. On-Prem: Managed Kubernetes Platform and Hadoop ecosystem. Why This Role is Different Direct Impact: Build AI tools that traders and quants use daily ...

infrastructure, and cloud-native tooling. Tech Stack Programming: Python (Java familiarity is a plus). AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and more. On-Prem: Managed Kubernetes Platform and Hadoop ecosystem. Why This Role is Different Direct Impact: Build AI tools that traders and quants use daily ...

Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, Arize, LangFuse, or other MLOps tools. • Experience with deploying ML models on SageMaker, KServe, or similar. Why Plexe? • Hard problems: we're automating the entire ML/AI lifecycle from data engineering to insights. • High ownership: first ...

containerisation (Docker, Kubernetes) and orchestration of multi-stage ML workflows. Hands-on experience with ML platforms and tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). ...

data processing frameworks. Proficiency with ML libraries such as PyTorch and TensorFlow. Experience with cloud platforms (AWS, EMR, Kubernetes, Docker) and ML platforms (Databricks, SageMaker). Familiarity with workflow management tools (e.g., Airflow). Strong understanding of software design principles, data structures, and design patterns. Ability to debug, test ...

/Knowledge Graph expertise - deep knowledge with Knowledge Graphs and vector databases Strong technical fluency - TypeScript/React, Langgraph/Langchain, neo4j, Docker, AWS (SageMaker, Bedrock, Hugging face), to name a few Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options ...

evaluation harnesses. Develop APIs, microservices and serverless workflows for scalable deployment. ML/LLM Engineering Work with AI+ML pipelines through Azure ML, AWS SageMaker, Vertex AI, Databricks, or Modal/Fly.io for lightweight LLM deployment. Utilize vector databases (Pinecone, Weaviate, Milvus, ChromaDB, pgVector) and embedding stores. Use AI-powered … Cohere Command R+, DeepSeek Frameworks: LangChain, LlamaIndex, Haystack, AutoGen, CrewAI Tools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, Humanloop Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, Modal Infra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, Redis Staffworx are a UK based Talent & Recruiting Partner, supporting ...