51 to 75 of 171 Permanent Amazon SageMaker Jobs

agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing More ❯

experience in MLOps, DevOps, or software engineering roles. Strong programming skills in Python and familiarity with ML frameworks. Extensive experience with AWS services (e.g., SageMaker, ECS, Lambda) and cloud environments. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Experience with version control systems and CI/CD pipelines. More ❯

statistical modelling, machine learning (supervised and unsupervised), deep learning, and MLOps. Proficiency in Python, SQL, and data science platforms such as Dataiku, Azure Synapse, SageMaker, or similar. Data Ecosystem Knowledge : Experience with cloud-native data platforms (e.g., AWS, Azure, GCP), scalable data pipelines, and version-controlled model deployment environments. More ❯

statistical modelling, machine learning (supervised and unsupervised), deep learning, and MLOps. Proficiency in Python, SQL, and data science platforms such as Dataiku, Azure Synapse, SageMaker, or similar. Data Ecosystem Knowledge : Experience with cloud-native data platforms (e.g., AWS, Azure, GCP), scalable data pipelines, and version-controlled model deployment environments. More ❯

statistical modelling, machine learning (supervised and unsupervised), deep learning, and MLOps. Proficiency in Python, SQL, and data science platforms such as Dataiku, Azure Synapse, SageMaker, or similar. Data Ecosystem Knowledge : Experience with cloud-native data platforms (e.g., AWS, Azure, GCP), scalable data pipelines, and version-controlled model deployment environments. More ❯

performing high quality work both independently, and with a team, in a fast-moving environment. DESIRED QUALIFICATIONS Familiarity with ML Hosting technologies such as SageMaker and NVIDIA Triton. Knowledge of monitoring and logging tools like ELK, Prometheus, Elasticsearch, Logstash and Kibana, PostgreSQL or other database engines. Demonstrated understanding of More ❯

agency contexts. Minimum 4 years of software engineering foundation experience in Python. Minimum 4 years of experience in ML/AI platforms including Databricks, SageMaker, Snowflake, and Vertex AI. Minimum 3 years of experience with AI frameworks (such as TensorFlow, PyTorch) and building and deploying AI models . Minimum More ❯

and LLM frameworks. End-to-End AI Delivery Design, build, and maintain scalable AI and LLM-based pipelines using AWS or Azure services (e.g., SageMaker, Azure ML, Databricks, OpenAI integrations). Oversee AI model lifecycles from data preprocessing and prompt engineering through to deployment and continuous monitoring in production More ❯

and LLM frameworks. End-to-End AI Delivery Design, build, and maintain scalable AI and LLM-based pipelines using AWS or Azure services (e.g., SageMaker, Azure ML, Databricks, OpenAI integrations). Oversee AI model lifecycles from data preprocessing and prompt engineering through to deployment and continuous monitoring in production More ❯

and LLM frameworks. End-to-End AI Delivery Design, build, and maintain scalable AI and LLM-based pipelines using AWS or Azure services (e.g., SageMaker, Azure ML, Databricks, OpenAI integrations). Oversee AI model lifecycles from data preprocessing and prompt engineering through to deployment and continuous monitoring in production More ❯

data versioning, quality management, and CI/CD pipelines Experience with cloud platforms (e.g., AWS or Azure) and data tools such as Terraform or SageMaker is a plus Ideally, some hands-on experience building and maintaining data pipelines in a production environment What's on Offer: Competitive salary More ❯

AWS Experience with containerization (e.g., Docker) and orchestration (e.g., Kubernetes) Familiarity with AI/ML concepts, frameworks (e.g., TensorFlow, PyTorch), and tools (e.g., AWS SageMaker, Azure ML) - What You Can Expect: A culture of integrity. At CACI, we place character and innovation at the center of everything we do. More ❯

especially in deploying AI models or microservices. Cloud Services: Familiarity with cloud platforms like AWS, Azure, or GCP. Experience with services such as AWS SageMaker, Google AI, or Azure Machine Learning is a plus. Serverless Architectures: Exposure to serverless architectures, ideally edge compute environments such as Cloudflare Workers. Problem More ❯

analytical person with a bias for action. What Technologies We Use: Python, dbtLabs, SQL, GitHub Actions (CI/CD) Terraform, Docker, MLOps Platform (VertexAI, Sagemaker and MLFlow) With ecobee, you'll have the opportunity to: Be part of something big: Get to work in a fresh, dynamic, and ever More ❯

days a week We seek a skilled and proactive Senior Platform Engineer to design, build, and support scalable cloud infrastructure and automation pipelines on Amazon Web Services (AWS). You will work closely with DevOps, Security, Data, and AI Application teams to ensure platform reliability, security, and performance. Your … development, staging, and production environments. Automate operational tasks, environment provisioning, and deployments using scripting languages such as Python, Bash, or PowerShell. Enable and maintain Amazon SageMaker environments for scalable ML model training, hosting, and pipelines. Integrate AWS Bedrock to provide foundation model access for generative AI applications, ensuring … Collaborate with security and compliance teams to implement best practices around IAM, encryption, logging, monitoring, and cost optimization. Implement and manage observability tools like Amazon CloudWatch, Prometheus/Grafana, or ELK for monitoring and alerting. Support container orchestration environments using EKS (Kubernetes), ECS, or Fargate. Contribute to incident response More ❯

with a track record of leading successful projects, preferably in a consulting environment. Expertise in cloud-based AI and Data platforms (Azure AI, AWS SageMaker, Google AI), MLOps frameworks, and big data technologies (Databricks, Snowflake, Hadoop). Exceptional project management skills, with a demonstrated ability to plan, execute, and More ❯

with a track record of leading successful projects, preferably in a consulting environment. Expertise in cloud-based AI and Data platforms (Azure AI, AWS SageMaker, Google AI), MLOps frameworks, and big data technologies (Databricks, Snowflake, Hadoop). Exceptional project management skills, with a demonstrated ability to plan, execute, and More ❯

practices, including GitHub Actions or GitLab CI 5+ years of experience with AWS services and Cloud-native architecture patterns, including ECS, Lambda, SQS, SNS, SageMaker, RDS, DynamoDB, IAM policies, security groups, and network security 3+ years of experience with Infrastructure as Code, including AWS CDK, Terraform, or CloudFormation 3+ More ❯

world can't wait. You Have: 5+ years of experience with AWS services and cloud-native architecture patterns such as ECS, Lambda, SQS, SNS, SageMaker, RDS, DynamoDB, IAM policies , security groups, and network security 3+ years of experience with containerization such as Docker, Kubernetes, ECS, and container orchestration 3+ More ❯

will contribute in this role: Architecting, building and maintaining GenAI processing pipelines/workflows in Python via technologies such as serverless functions, Airflow, MLflow, SageMaker, Bedrock, or other Working with Data and NLP Engineers and Data Scientists to automate experiments that bring ML and NLP research ideas to production … with programming in Python and Jupyter notebooks Professional experience in designing, building and managing bespoke GenAI solutions in cloud environments, utilising platforms such as Amazon Bedrock Experience in building NLP solutions while consuming LLMs, either directly from third party APIs or directly from repositories such as Hugging Face Strong … fundamental technical expertise in cloud-native technologies, such as AWS Lambda, API Gateway, SageMaker Studio, Amazon ECR, CDK, or equivalent Experience in leading/mentoring NLP/ML/GenAI engineering teams Experience in working in teams with data scientists and data engineers, for building automated pipelines for More ❯

s Degree -6+ years of relevant experience -Geospatial experience Desired: -Experience with Python, R, SQL, or SAS -Experience with Git -Experience with AWS Sagemaker -Experience with statistics, NLP, Markov-Chain modeling, Linear Algebra, or TensorFlow This opportunity is located in Springfield, VA and requires a TS/SCI More ❯

right approach Previous experience developing real-world ML products in areas like demand forecasting, optimisation, or computer vision Comfortable working with AWS services (e.g. SageMaker, Lambda) Strong grasp of statistics and modelling, with the ability to turn raw data into actionable insight Willingness to learn the basics of backend More ❯

right approach Previous experience developing real-world ML products in areas like demand forecasting, optimisation, or computer vision Comfortable working with AWS services (e.g. SageMaker, Lambda) Strong grasp of statistics and modelling, with the ability to turn raw data into actionable insight Willingness to learn the basics of backend More ❯

right approach Previous experience developing real-world ML products in areas like demand forecasting, optimisation, or computer vision Comfortable working with AWS services (e.g. SageMaker, Lambda) Strong grasp of statistics and modelling, with the ability to turn raw data into actionable insight Willingness to learn the basics of backend More ❯

and colleagues from the Data Science chapter at Lyst. Our main tools include Python with frameworks like SKLearn, TensorFlow, and PyTorch, operating within AWS Sagemaker where possible. We emphasize clean, documented, well-tested, and reviewed code, supported by our tooling and culture. This role offers a hands-on, high More ❯