1 to 25 of 40 Amazon SageMaker Jobs

with the expectation to be in the London office 1-2 times per week. Key Responsibilities Deploy ML models as real-time endpoints using Amazon SageMaker * Build and manage batch inference pipelines * Implement CI/CD workflows for ML using Git-based processes * Containerize applications using Docker * Monitor … CloudWatch * Automate data pipelines and feature workflows using Python & SQL * Ensure secure access and governance using AWS IAM and best practices Core AWS Stack Amazon SageMaker | Amazon S3 | Amazon Redshift | AWS Lambda | Amazon CloudWatch | AWS IAM What We're Looking For Strong hands-on experience ...

Docker, Kubernetes desirable) Model packaging and REST APIs Cloud & Tools (Any combination) AWS/Azure/GCP analytics and ML services MLflow, Azure ML, SageMaker, Vertex AI Version control (Git) Domain & Soft Skills Strong analytical and problem solving skills Ability to explain complex data science concepts in simple business ...

Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/Bedrock, Google Vertex AI API-led architectures and microservices Security, governance, and responsible AI Frameworks ...

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

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

record building and maintaining CI/CD pipelines (GitHub Actions, CircleCI, Jenkins, GitLab CI) • Experience with MLOps and supporting ML model deployment workflows (AWS Sagemaker, Lambda, containerized deployments) • Proficiency in scripting and automation (Python, Bash, Go) • Strong experience with monitoring and observability tools (CloudWatch, Prometheus, Grafana, Datadog, Sentry ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

with LLMs/GenAI frameworks (LangChain, RAG, prompt engineering, etc.) Experience in cloud (AWS/Azure/GCP) · Experience in MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, etc.) API development experience Techno-Functional Capabilities Ability to translate business requirements into technical AI designs Strong solution architecture capability Experience designing ...

from feature engineering to deployment and monitoring Build and maintain data pipelines and production workflows using Python, TensorFlow, PyTorch, scikit-learn, AWS (S3, Lambda, SageMaker, Step Functions, Bedrock), Snowflake, and Dataiku Apply MLOps best practices, including CI/CD, automated testing, model versioning, and observability Define deployment standards ...

models using Python, PyTorch and modern ML frameworks Work with large datasets to train, evaluate and optimise models Implement and scale solutions on AWS (SageMaker, Bedrock, Lambda, etc.) Contribute to generative AI initiatives using Hugging Face and open-source models Collaborate with data engineers, architects and stakeholders to deliver ...

more cloud platforms or third-party technologies such as Google PaLM and Vertex AI, Azure OpenAI Services and Azure ML, AWS Bedrock and SageMaker, Dataiku, Databricks, Snowflake Snowpark and Snowflake Cortex, and DataRobot. Experience architecting scalable, high-performance, and cost-optimised AI and ML solutions using serverless technologies, containerised ...

deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering ...

Machine Learning Architect/GenAI Architect Hands-on expertise with LLMs, RAG, LangChain, LangGraph, prompt engineering Strong cloud experience: Azure OpenAI, AWS Bedrock/SageMaker or GCP Vertex AI Experience with Kubernetes, Docker, microservices, API integration Strong knowledge of Python, MLOps, LLMOps, CI/CD, model monitoring Experience delivering ...

Architect Strong hands-on expertise with LLMs, RAG architectures, LangChain, LangGraph, and prompt engineering Deep cloud knowledge including Azure OpenAI, AWS Bedrock/SageMaker, or GCP Vertex AI Experience with Kubernetes, Docker, microservices architectures, and API integrations Proficiency in Python, MLOps, LLMOps, CI/CD pipelines, and model monitoring ...

similar OR packages Production ML/optimisation software experience - you've shipped models that run at scale Cloud platform experience (AWS preferred); familiarity with SageMaker, DVC, GitHub Actions a bonus Strong SQL and data engineering fundamentals Experience in airline, aviation, transport, or engineering/maintenance environments is highly desirable ...

Generative AI models, LLMs, and agentic frameworks. Collaborate with stakeholders to define problem statements and solution approaches. Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. Ensure high-quality delivery and adherence to best practices ...

native tooling. Architect and develop cutting-edge platform services for AI-driven trading. Tech Stack Programming: Python AWS: S3, Kinesis, Glue, Lambda, Step Functions, SageMaker, and Databricks On-Prem: Managed Kubernetes Platform and Hadoop ecosystem. What we are looking for 5 – 10 years of experience in data engineering, ideally ...

Generative AI models, LLMs, and agentic frameworks. •Collaborate with stakeholders to define problem statements and solution approaches. •Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. •Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. •Ensure high-quality delivery and adherence to best practices ...

e.g. seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g. MLflow) Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker ...

related field. Three to Five years related work experience in AWS cloud machine learning or a similar AI platforms, with familiarity in AWS Sagemaker, Lambda, S3, Athena, etc. Proficiency in one or more programming languages, including Python (preferred) or R, Spark, and other modern data science tools. Working knowledge ...

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: Expert level 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 ...

endpoints Key details: • Salary: £80,000–£110,000 + discretionary bonus • Working: Hybrid, 3 days per week in London • Stack: Python, MLflow, AWS (SageMaker), CDK, Docker • Visa: Cannot sponsor Interested? Please apply below. ...

tokenization etc) Strong knowledge of API/Microservices , Async programming, multithreading, performance, reliability, caching, event driven design, data pipelines, workflows, queues Hands-on with Amazon SageMaker for building, training, and deploying scalable machine learning models in cloud. Experience of Building rapid applications using FastAPI and Streamlit, Matplotlib, seaborn ...

Sourcegraph & Meta. 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 ...