1 to 25 of 31 Remote Amazon SageMaker Jobs

in Python, Java, or C++ Familiarity with TensorFlow, PyTorch, Hugging Face, Scikit-learn, and related ML libraries Experience with Docker, Kubernetes, and cloud AI platforms such as AWS Bedrock, Sagemaker, Azure ML, or GCP Vertex AI Working knowledge of data tools such as Spark, Pandas, SQL/NoSQL databases Security: TS clearance required Nice to Have Experience with LangChain More ❯

React, Angular, DevOps, CI/CD, Git, microservices, REST API, Kafka, Kinesis, distributed systems, RAG pipelines, LangChain, Bedrock, Hugging Face, Qdrant, computer vision, deep learning, neural networks, TensorFlow, PyTorch, SageMaker, Bedrock, security clearance, Top Secret, Secret, DevSecOps, containerization, automation, data engineering, cloud architecture, scalable systems, federal contracting, cleared engineer More ❯

agent solutions that integrate with enterprise systems and cloud platforms. Develop and optimize RESTful and GraphQL APIs to facilitate AI-driven interactions. Utilize AWS services (Lambda, S3, API Gateway, SageMaker, DynamoDB, ECS, etc.) to deploy scalable AI solutions. Implement Full Stack JavaScript (Node.js, React.js, Express, TypeScript, Next.js, etc.) applications to support AI-driven interfaces. Work closely with data scientists 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 ❯

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 ❯

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 ❯

tuning or inference optimization. Understanding of vector databases (e.g., Qdrant, Pinecone) and semantic search techniques. Use of MLOps tools for CI/CD pipelines in AI (e.g., MLflow, Kubeflow, SageMaker). AI for Systems Engineering Experience working with SysML, MBSE tools, or digital engineering pipelines. Understanding of how to map or extract system design intent from technical documentation using More ❯

updates in development, integration and production environments. Set up, integrate, and maintain a scalable, stable set of CI/CD tools to support development, testing, and security scanning. Implement Amazon CloudWatch, Splunk and other third party monitoring solutions to provide continuous monitoring capabilities, track all aspects of the system, infrastructure, performance, application errors and roll up metrics. Analyze functional … with standard concepts, practices, and procedures such as NIST, FISMA, FedRamp and Common Criteria regulations and standards. Familiarity with the MLOps, machine learning lifecycle and product landscape, for example: Amazon SageMaker, Apache Airflow, Looker, Trifacta etc. You don't need to be an expert in all these. Working knowledge of Linux Professional Skills: Excellent communication and interpersonal skills More ❯

higher certification. Willingness to do a programming challenge during the interview process. Experience with Jupyter Notebooks, Python Data Science Libraries. Experience with ML-OPS and related tools (e.g., MLFLOW, Sagemaker, Bedrock) and ability to build interactive, insightful dashboards for monitoring ML models. Place of Performance: Hybrid work in San Antonio, TX. Desired Skills (Optional) Experience with NOSQL databases such More ❯

to support decisions across multiple business areas, including marketing, sales, claims, retention, customer behavior, fraud detection, and customer servicing. Deploy machine learning models into production using AWS services, including SageMaker, S3, Feature Store, ensuring scalable, reliable, and monitored solutions that directly support key business processes. Collaborate with product management and engineering teams to integrate data-driven insights and deploy More ❯

updates in development, integration and production environments. Set up, integrate, and maintain a scalable, stable set of CI/CD tools to support development, testing, and security scanning. Implement Amazon CloudWatch, Splunk and other third party monitoring solutions to provide continuous monitoring capabilities, track all aspects of the system, infrastructure, performance, application errors and roll up metrics. Analyze functional … with standard concepts, practices, and procedures such as NIST, FISMA, FedRamp and Common Criteria regulations and standards. Familiarity with the MLOps, machine learning lifecycle and product landscape, for example: Amazon SageMaker, Apache Airflow, Looker, Trifacta etc. You don't need to be an expert in all these. Working knowledge of Linux Professional Skills: Excellent communication and interpersonal skills More ❯

will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies - Python, GitHub, Sagemaker, SQL, AWS and more - to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through 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 ❯

of AI frameworks (TensorFlow, PyTorch, Keras) Experience with NLP and computer vision models Strong understanding of machine learning algorithms and statistical modeling Experience with cloud-based AI platforms (AWS SageMaker, Google Cloud AI Platform) Excellent problem-solving and communication skills Qualifications Master's degree in Computer Science, Artificial Intelligence, or related field Certified AI Engineer or related certification (optional 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 ❯

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 ❯

and S3. • Manage dashboards and reporting tools like Qlik Sense and Splunk, linked with AWS data services. • Support AI/ML initiatives with cloud-hosted experiments and pipelines (e.g., SageMaker optional). AWS Technologies Required: • EC2, S3, RDS, API Gateway, CloudFront, CloudWatch, IAM • DevOps experience with Jenkins, SonarQube, Spring Boot, Mulesoft 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 ❯

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 ❯