1 to 25 of 36 Remote Permanent Amazon SageMaker Jobs

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) - SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) - SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) - SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB 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 ❯

the requests library. Exposure to Lang Chain or MCP. Experience with one or more of the following AI Platforms: AWS Sage Maker Google Vertex AI OpenAI API Azure OpenAI Amazon Bedrock Cohere API Databricks Azure Machine Learning Replicate Hugging Face APIs Education: Bachelors degree in Computer Science, Software Engineering, or a related technical field. Other Information: CGI is required More ❯

delivery • Proven track record deploying ML systems in production at scale (batch and/or real-time) • Strong technical background in Python and ML engineering tooling (e.g. MLflow, Airflow, SageMaker, Vertex AI, Databricks) • Understanding of infrastructure-as-code and CI/CD for ML systems (e.g. Terraform, GitHub Actions, ArgoCD) • Ability to lead delivery in agile environments-balancing scope 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 ❯

etc) Build efficient data pipelines between on-premise and cloud environments to handle text and audio data processing loads for ML models Deploy NLP models in cloud environments (AWS SageMaker) through Jenkins Design and implement MLflow and other ML Ops applications to streamline ML workflows which adhere to strict data privacy and residency guidelines Communicate your work throughout the … Huggingface; strong programming skills in Java are a plus Expert level know-how of ML Ops systems, data pipeline design and implementation, and working with ML platforms (preferably AWS SageMaker) Strong analytical and problem-solving abilities, with a keen eye for detail and accuracy Curiosity and a strong growth mindset with a demonstrable history of learning quickly in a More ❯

learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt, Prefect Cloud & Deployment Platforms: AWS SageMaker, Azure ML, Google Vertex AI APIs & Orchestration: OpenAI API, Anthropic Claude, Weaviate, FastAPI (for AI applications) MLOps & Experimentation: Weights & Biases, DVC (Data Version Control), Docker, Kubernetes General 2+ years More ❯

Terraform, GitHub, and VS Code for pipeline deployment. Proven leadership in developing high-performing data teams. Strong SQL and familiarity with analytics tools such as Alteryx, AWS Athena, Quicksight, Sagemaker, Tableau, and Power BI. Excellent communication and stakeholder management skills. Ability to write clear technical documentation and define user stories with appropriate acceptance criteria. Desirable: Experience in real-time More ❯

Terraform, GitHub, and VS Code for pipeline deployment. Proven leadership in developing high-performing data teams. Strong SQL and familiarity with analytics tools such as Alteryx, AWS Athena, Quicksight, Sagemaker, Tableau, and Power BI. Excellent communication and stakeholder management skills. Ability to write clear technical documentation and define user stories with appropriate acceptance criteria. Desirable: Experience in real-time More ❯

Terraform, GitHub, and VS Code for pipeline deployment. Proven leadership in developing high-performing data teams. Strong SQL and familiarity with analytics tools such as Alteryx, AWS Athena, Quicksight, Sagemaker, Tableau, and Power BI. Excellent communication and stakeholder management skills. Ability to write clear technical documentation and define user stories with appropriate acceptance criteria. Desirable: Experience in real-time More ❯

big data technologies and cloud-based technologies AWS Services, State Machines, CDK, Glue, TypeScript, CloudWatch, Lambda, CloudFormation, S3, Glacier Archival Storage, DataSync, Lake Formation, AppFlow, RDS PostgreSQL, Aurora, Athena, Amazon MSK, Apache Iceberg, Spark, Python ONSITE: Partially onsite 3 days per week (Tue, Wed, Thurs) and as needed. Standard work hours: 8:30 AM - 5:00 PM Required Qualifications … related degree 6 years-of application development, systems testing Nice to have: AWS Redshift, Databricks- delta Lake, Unity catalog, Data Engineering and processing using Databricks, AI and Machine Learning Amazon Bedrock, AWS Sagemaker, Unified Studio, R Studio/Posit Workbench, R Shiny/Posit Connect, Posit Package Manager, AWS Data Firehose, Kafka, Hive, Hue, Oozie, Sqoop, Git/ More ❯

libraries Solid understanding of supervised and unsupervised learning techniques Experience in demand prediction, optimisation, or computer vision is advantageous Comfortable working with cloud platforms (preferably AWS) and services like SageMaker or Lambda Strong mathematical and statistical foundations, with a sharp eye for patterns and insights Willingness to build basic backend development skills (Python/Django or Go) to support More ❯

Proficiency in Python AI libraries is essential, with preferred expertise in demand prediction, computer vision, or optimisation. Familiarity with the AWS cloud platform, particularly its AI/ML services (SageMaker and Lambda) and related data processing tools, is also required. This is a fantastic opportunity for a Senior Data Scientist to join a company at an exciting time of … Python. Proficient as a Data Scientist with knowledge of Python AI libraries. Expertise in demand prediction, computer vision, or optimisation (preferred). Familiarity with AWS AI/ML services (SageMaker, Lambda). Academic Excellence (Russel Group University or Internship at a leading Tech company) Reference Number: BBBH257746 To apply for this role or for to be considered for further More ❯

Proficiency in Python AI libraries is essential, with preferred expertise in demand prediction, computer vision, or optimisation. Familiarity with the AWS cloud platform, particularly its AI/ML services (SageMaker and Lambda) and related data processing tools, is also required. This is a fantastic opportunity for a Senior Data Scientist to join a company at an exciting time of … Python. Proficient as a Data Scientist with knowledge of Python AI libraries. Expertise in demand prediction, computer vision, or optimisation (preferred). Familiarity with AWS AI/ML services (SageMaker, Lambda). Academic Excellence (Russel Group University or Internship at a leading Tech company) Reference Number: BBBH257746 To apply for this role or for to be considered for further More ❯

Proficiency in Python AI libraries is essential, with preferred expertise in demand prediction, computer vision, or optimisation. Familiarity with the AWS cloud platform, particularly its AI/ML services (SageMaker and Lambda) and related data processing tools, is also required.This is a fantastic opportunity for a Senior Data Scientist to join a company at an exciting time of growth … Python. Proficient as a Data Scientist with knowledge of Python AI libraries. Expertise in demand prediction, computer vision, or optimisation (preferred). Familiarity with AWS AI/ML services (SageMaker, Lambda). Academic Excellence (Russel Group University or Internship at a leading Tech company) Reference Number: BBBH257746 To apply for this role or for to be considered for further More ❯

and Terraform. Understanding of data governance, lineage tools, and cloud-based data architectures. Skilled in a range of analytics and BI tools (e.g., SQL, Alteryx, Power BI, Tableau, AWS SageMaker, QuickSight). Strong documentation, communication, and stakeholder management skills. Adept at managing multiple priorities in a fast-paced environment, with strong attention to detail. Desirable: Familiarity with AWS Lake More ❯

and optimize AWS-based data infrastructure, including S3 and Lambda, as well as Snowflake. Implement best practices for cost-efficient, secure, and scalable data processing. Enable and optimize AWS SageMaker environments for ML teams. Collaborate with ML, Data Science, and Reporting teams to ensure seamless data accessibility. Implement data pipeline monitoring, alerting, and logging to detect failures and performance More ❯

solutions in complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React; familiarity More ❯

multi-modal models that combine vision and language Strong grasp of data-centric AI practices - annotation tooling, prompt evaluation, and dataset curation Familiarity with MLOps tools (e.g. Weights & Biases, SageMaker, MLflow) Experience working in regulated sectors like insurance, banking, or property What You'll Be Doing This is a hands-on, high-impact role - you'll be building production … image segmentation Apply NLP to real-world business problems - summarisation, entity recognition, information extraction, and more Train and deploy models at scale using AWS - including Lambda, EC2, S3, and SageMaker Meet with enterprise clients to explore problems, present ideas, and share results Prototype fast, test often, and get working solutions into the hands of users Work cross-functionally with More ❯

multi-modal models that combine vision and language Strong grasp of data-centric AI practices - annotation tooling, prompt evaluation, and dataset curation Familiarity with MLOps tools (e.g. Weights & Biases, SageMaker, MLflow) Experience working in regulated sectors like insurance, banking, or property What You'll Be Doing This is a hands-on, high-impact role - you'll be building production … image segmentation Apply NLP to real-world business problems - summarisation, entity recognition, information extraction, and more Train and deploy models at scale using AWS - including Lambda, EC2, S3, and SageMaker Meet with enterprise clients to explore problems, present ideas, and share results Prototype fast, test often, and get working solutions into the hands of users Work cross-functionally with More ❯

Desirable experience: Familiar with Terraform, from a developer perspective. Previous work in financial services, healthcare, or similarly regulated data environments. Experience with LLMs, voice agents, or tools like AWS SageMaker, AWS Bedrock, or ElevenLabs. Exposure to soft real-time systems or distributed system architectures. Knowledge of OAuth, SQS, or running containers in production. More ❯

Desirable experience: Familiar with Terraform, from a developer perspective. Previous work in financial services, healthcare, or similarly regulated data environments. Experience with LLMs, voice agents, or tools like AWS SageMaker, AWS Bedrock, or ElevenLabs. Exposure to soft real-time systems or distributed system architectures. Knowledge of OAuth, SQS, or running containers in production. JBRP1_UKTJ More ❯