1 to 25 of 30 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 ❯

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 ❯

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 ❯

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 ❯

predictive modeling and forecasting, statistics). • Proficiency in tools and languages such as Graph DBs, PostgreSQL/SQL, Python, or Java. • Experience using ML algorithms packages contained in AWS SageMaker or open-source libraries (Python, C++, etc.) • Experience developing, verifying, and monitoring AI/ML Models • Familiarity with DevOps processes and code versioning tools such as git • TS/… processes • Experience with using the Joint Enterprise Modeling and Analytics (JEMA) framework or Apache NiFi to develop data processing workflows • Experience in AWS services including but not limited to Sagemaker, S3, EMR, and IAM. CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range 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 ❯

evidenced by Attachment II, Proposed Project Person Skill Summary Sheet, and resume: At least three (3) to five (5) years of experience with AWS cloud platform and services like Amazon Elastic Compute Cloud (EC2)/virtual machines (VM) Instances, S3/Cloud Storage, Serverless (AWS Lambda, Cloud Functions), and IAM (Identity & Access Management). At least three (3) to … and debug basic web applications with familiarity with APIs Representational State Transfer (REST) and using Python, Node.js, or C#. At least three (3) years of experience using Docker, Kubernetes Amazon Elastic Kubernetes Service (EKS) , and container orchestration. At least three (3) to five (5) years of experience with structured query language (SQL) and/or non-SQL (NoSQL) databases … CloudWatch Logs, CloudTrail, or third-party tools like Splunk. Scripting experience with Bash, PowerShell, or equivalent. Experience with Artificial Intelligence/Machine Learning (AI/ML) cloud services (e.g., SageMaker) and multi-cloud architecture. The proposed project person will be required to adhere to the Client's hybrid working model, currently working on-site 2-3 days per week More ❯

Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semantic search, or event-driven systems like Kafka We … everyone, regardless of background, gender identity, sexual orientation, disability status, ethnicity, belief, age, family or parental status, and any other characteristic. Python, Apache Kafka, Semantic search, PyTorch, Algorithms, Docker, Amazon Web Services, Language Models, Service support, Back End, Machine learning, DevOps Engineering, Monitoring, Cloud, Labour market, Pipelines, Database, Realtime, Infrastructure, Recommender system, Agile Environment, Software Use, Terraform, API, Making More ❯