1 to 25 of 36 Remote Amazon SageMaker Jobs

maintaining cloud-based platforms and infrastructure, with a focus on AWS. Hands on experience with AWS, including practical delivery across core services such as Amazon EC2, Amazon EKS, Amazon RDS, Amazon Redshift, Amazon S3, Amazon VPC, AWS Identity and Access Management (IAM), AWS Lambda … identity management in cloud environments, including AWS-specific best practices. Familiarity with monitoring, logging, and alerting tools (e.g., Prometheus, Grafana, the ELK stack, Amazon CloudWatch, and AWS X-Ray). Experience with version control systems (e.g., Git) and scripting languages (e.g., Python, Bash, Go). Ability to troubleshoot ...

Description WTW is seeking a Cloud Platform Engineer -AWS to design, build, and operate the enterprise-scale Amazon Web Services (AWS) compute platform that supports our global business services. In this role, you will deliver secure, scalable, and highly automated cloud services through Infrastructure as Code, platform standards, governance … scale, multi-account AWS environment governed through AWS Organizations, organizational units (OUs), and AWS Control Tower. Design, implement, and manage AWS compute infrastructure, including Amazon EC2, Auto Scaling groups, Elastic Load Balancing, Amazon EBS, and standardized machine images (AMIs) built with EC2 Image Builder. Partner with network ...

that fuel analytics, AI/ML, and data-driven operations.* Design and build high-performance data integration solutions: Use AWS Glue, AWS Step Functions, Amazon EventBridge, and AWS Database Migration Service (DMS) to orchestrate ingestion, transformation, and movement of data across on-premises and cloud sources into Amazon … Design and oversee the delivery of secure lakehouse and warehouse architectures: Implement logical and physical data models, data quality controls, and governance practices using Amazon S3 (data lake), AWS Lake Formation, Amazon Redshift, and Amazon Athena to ensure trusted data.* Ability to design AI/ML-enabled ...

cloud governance engagements. You will own the client-facing pre-sales cycle for AI/GenAI work – running scoping calls, designing solutions on Amazon Bedrock, SageMaker and associated services, estimating effort, writing commercially sound Statements of Work, and providing ongoing strategic advisory to customers. Beyond AI, you will … stay technically current and want to get their hands dirty alongside the delivery team. Key Responsibilities Design AI/GenAI solutions on AWS (Amazon Bedrock, Bedrock Agents, Amazon Q, SageMaker, associated serverless and data services) and produce architecture documentation for customer engagements. Scope and design broader ...

scaling AI solutions using at least one major cloud platform: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker)* Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK* Hands-on experience ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ML services (SageMaker, Vertex AI, or Azure ML) Strong software engineering practices: version control, testing, CI/CD MSc or PhD in Computer Science, Machine Learning ...

Expertise with modern data platforms (e.g., BigQuery/Databricks) and data processing workflows (ETL, pipelines). Excellent experience with cloud hosted AI platforms (Bedrock, Sagemaker, VertexAI) Strong problem-solving abilities, with the capacity to learn quickly and adapt in a fast-paced environment. Excellent communication and a drive ...

Machine Learning, or a related technical discipline. Public writing, talks, or threads about building with AI. MLOpsand model serving experience (BentoML,MLflow, Vertex AI, SageMaker). Streaming and batch ingestion pipelines (Spark, Airflow, Beam, Glue). Healthcare or life sciences domain exposure. AWS Professional certification or other relevant industry ...

calibration)• Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust)MLOps & LLMOps• Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector)• Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks• Exposure to fine-tuning ...

Terraform, Jenkins, Cloudformation or any other IAAC. Proven Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer on AWS Sagemaker and similar tools. Knowledge and experience with CI/CD tools. Strong hands-on technical skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting ...

tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required. Understanding model evaluation methods and metrics. Ability to operationalize non-technical ideas into relevant research designs, features ...

Notebooks Strong understanding of predictive modelling and machine learning techniques Experience with NLP and Large Language Models (LLMs) Familiarity with AWS services, including S3, SageMaker and Lambda Experience or knowledge of Microsoft Fabric Understanding of the machine learning model development and deployment lifecycle Strong analytical and problem-solving abilities ...

Experience Proven experience designing and deploying production-grade AI/ML or LLM systems . Expertise with AWS or Azure AI services (e.g., Bedrock, SageMaker, OpenAI, Cognitive Services). Strong Python programming skills with hands‐on experience using frameworks like Autogen and LangGraph . Solid grounding in MLOps , containerisation ...

code, not just notebooks.* Hands-on experience with Snowflake (or a comparable cloud data warehouse — BigQuery, Redshift, Databricks).* Experience deploying models on AWS (SageMaker, Lambda, ECS, or similar).* Solid grounding in statistics, experimentation, and causal inference — you know when a correlation isn't enough.* Track record ...

infrastructure security, reliability and operational best practice. Desirable Experience The following would be advantageous: MLOps or LLMOps experience. Experience with platforms such as SageMaker, Kubeflow or ZenML . Extensive on-premises Kubernetes deployment experience. Prometheus or comparable observability platforms. AWS Karpenter. AWS Compute Optimizer. Experience operating highly distributed systems. ...

infrastructure security, reliability and operational best practice. Desirable Experience The following would be advantageous: MLOps or LLMOps experience. Experience with platforms such as SageMaker, Kubeflow or ZenML . Extensive on-premises Kubernetes deployment experience. Prometheus or comparable observability platforms. AWS Karpenter. AWS Compute Optimizer. Experience operating highly distributed systems. ...

Desirable Skills Experience with the Model Context Protocol (MCP) or similar tool-use/agent protocols. Familiarity with AWS services (Lambda, SQS/SNS, SageMaker, Bedrock, S3). Experience with vector databases, embeddings, or retrieval‐augmented generation (RAG) patterns. Understanding of prompt engineering, evaluation, and the practical challenges ...

Technical Knowledge: Strong understanding of modern AI/ML technologies and cloud-based solutions. Tools & Platforms: Familiarity with Snowflake, Databricks, Azure AI Foundry , AWS SageMaker, and other leading platforms. Data Science Expertise: Knowledge of data science fundamentals, solution lifecycles, and MLOps methodology. Generative AI Knowledge: Experience with LLMs, neural ...

enhance your day-to-day work. Technologies and Tools Python Machine learning frameworks (e.g. PyTorch, TensorFlow, scikit-learn) ML/MLOps tooling (e.g. SageMaker, MLflow, TFServing) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) CI/CD tooling and best practices Streaming and batch data systems (e.g. ...

business-critical services. - GitLab, PostgreSQL, NGINX, VPN/OpenVPN, Elastic/Kibana and Windows administration. Desirable - C#, .NET, JavaScript, React, Vue.js and microservices. - AWS SageMaker, AI/LLM integrations and Python-based analytics tooling. - Enterprise cloud architecture and secure-by-design principles. - Disaster recovery and business continuity planning. - Experience ...

cloud security for services and infrastructure. Experience with Kubernetes (K8S) is a plus. Cloud Expertise: Familiarity with AI infrastructure on AWS and GCP, including Sagemaker, Vertex, Triton, and GPU computing. Bonus Points: Experience with Airbyte is a significant advantage. Perks and Benefits: Fully Remote: Freedom to work from anywhere ...