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Aws Sagemaker Jobs (NOW HIRING)

CYNET SYSTEMS

AI/ML Engineer

Aliso Viejo, CA · On-site

$52 - $57/hr

AWS SageMaker (Training, Deployment, Endpoints) - 2-3+ years (Hands-on). * Data Preprocessing & Feature Engineering - 3+ years. * Model Evaluation Techniques - 3+ years. * Version Control (Git) - 2+ ...

Hudson Manpower

DATA ENGINEER IV

Cincinnati, OH · On-site

$68 - $70/hr

Must Have Python SQL Nice To Have AWS Sagemaker DBT Snowflake What You'll Do Squad: Machine Learning Data Enablement squad in the Data Insights Tribe Required: In office 4 days a week minimum (Monday ...

Spear Staffing

MLOps / AI Ops Engineer

Houston, TX · On-site

$50.25 - $69/hr

You will work with Amazon SageMaker, AWS MLOps, and other relevant technologies to ensure the successful deployment and operation of machine learning systems. This role requires a strong background ...

New

Software People, Inc.

Senior AWS Developer

Raleigh, NC · On-site

AWS Glue, AWS Lambda, EMR, Athena, Amazon Managed Service for Apache Flink,AWS Step Functions, AWS SageMaker Required 7 Years * Experience with DevOps practices and automation tools Required 7 Years

Purple Drive

AI/ML Architect (AWS MLOps)

Culver City, CA · On-site

$70.75 - $93/hr

AWS Sagemaker, GCP Vertex AI, Databricks). * 3+ years: ML & Data Pipeline Orchestration (Eg. Kubeflow, Apache Airflow). * 2+ years: ML Feature Store Tools (Eg. Tecton, Databricks, FeatureForm). * 3+ ...

SWBC

Data Scientist II

Shavano Park, TX · On-site

$80 - $100/hr

Build and maintain ML/AI experiment workflows using Hex for prototyping and exploration, and AWS SageMaker and MLflow for experiment tracking, feature engineering, and model versioning. * Develop and ...

New

Innosoul inc

AWS/ETL Developer

Raleigh, NC · On-site

AWS Glue, AWS Lambda, EMR, Athena, Amazon Managed Service for Apache Flink,AWS Step Functions, AWS SageMaker Required 10 Years Data Ingestion & storage : S3, Amazon Kinesis Data Streams, Amazon ...

SWBC

Data Scientist II

San Antonio, TX · On-site

Build and maintain ML/AI experiment workflows using Hex for prototyping and exploration, and AWS SageMaker and MLflow for experiment tracking, feature engineering, and model versioning. * Develop and ...

SWBC

Senior Data Scientist

San Antonio, TX

Your daily work will center on developing and deploying within SWBC Intelligence, our multi-model AI orchestration platform spanning AWS Bedrock, AWS Sagemaker, alongside Hex for experimentation and ...

VIVA USA INC

AWS Senior Developer

Raleigh, NC · On-site

AWS Glue, AWS Lambda, EMR, Athena, Amazon Managed Service for Apache Flink,AWS Step Functions, AWS SageMaker - Required - 10 Years Data Ingestion & storage : S3, Amazon Kinesis Data Streams, Amazon ...

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How much do aws sagemaker jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for aws sagemaker in the United States is $54.05, according to ZipRecruiter salary data. Most workers in this role earn between $38.70 and $64.42 per hour, depending on experience, location, and employer.

What is an AWS SageMaker?

An AWS SageMaker job typically refers to a role focused on building, training, and deploying machine learning models using Amazon SageMaker. Professionals in this role work with data preprocessing, model optimization, and cloud-based machine learning workflows. Responsibilities may include automating ML pipelines, monitoring performance, and integrating SageMaker with other AWS services. Knowledge of Python, TensorFlow, PyTorch, and AWS services is often required.

What does an AWS SageMaker do?

Day-to-day responsibilities for AWS SageMaker professionals typically include building, training, and deploying machine learning models using the SageMaker platform, preprocessing data, and monitoring the performance of deployed models. You'll often collaborate with data engineers, software developers, and business stakeholders to understand project requirements and deliver solutions that meet business objectives. Routine tasks may also involve tuning model hyperparameters, optimizing resource usage, and ensuring data security and compliance within AWS environments. This hands-on, collaborative workflow provides the opportunity to directly impact business outcomes while continuously developing your technical expertise.

What are the key skills and qualifications needed for an AWS SageMaker?

To excel in an AWS SageMaker-focused role, you need strong expertise in machine learning, data science, and cloud computing, often supported by a degree in computer science or a related field. Experience with AWS SageMaker, other AWS services (like S3 and Lambda), and certifications such as AWS Certified Machine Learning – Specialty are highly valued. Strong analytical thinking, problem-solving abilities, and effective communication skills help set candidates apart. Mastery of these areas ensures successful design, deployment, and management of scalable AI/ML solutions in dynamic business environments.

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Aws Sagemaker jobs near you
Infographic showing various Aws Sagemaker job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $112,422 per year, or $54 per hour.

Senior AWS Bedrock & SageMaker Developer

Programmers.io

San Antonio, TX • On-site

Contractor

Re-posted 13 days ago

Job description

Descriptions:
"• Develop, integrate, and optimize Generative AI applications using AWS Bedrock, including prompt engineering, RAG implementation, and AI agent workflows.
• Create and optimize prompts for LLMs
• Work with Amazon Bedrock APIs for model inference
• Develop backend services using Python / Node.js
• Enable real-time and streaming AI responses
• Build AI solutions using Bedrock Knowledge Bases
• Integrate with data sources (S3, databases, enterprise systems)
• Implement vector search and embeddings
• Design and build AI agents using Bedrock Agents
• Implement multi-step workflows and task automation
• Integrate external APIs/tools into AI workflows
• Work with core AWS services:
o IAM (security & access control)
o S3 (data storage)
o Lambda (serverless compute)
o API Gateway (service exposure)
• Deploy scalable and secure AI solutions
• Implement guardrails and content filtering
• Ensure data privacy, compliance, and safe AI usage
• Optimize token usage and model selection
• Monitor and control Bedrock usage costs
• Convert business requirements into AI-driven solutions
• Manage and utilize SageMaker Feature Store for reusable feature engineering
• Monitor model performance and detect data drift in production systems
• Maintain and retrain models for continuous performance improvement
• Track experiments, metrics, and ensure model reproducibility
• Integrate SageMaker with AWS services like S3, IAM, Lambda, and CloudWatch
• Optimize infrastructure, performance, and cost of ML workloads
• Collaborate with cross-functional teams to design and deliver ML solutions"
"Generative AI & LLM Fundamentals, Prompt Engineering, Bedrock API and SKD usage, RAG, AI Agents and workflow design,
Programming skill (Python, APIs, Microservice), AWS core knowledge (IAM, S3, Lambda, API Gateway), Application integration skills, Vector databases, CI/CD for AI Apps.
Understanding of ML life cycle, Strong coding in Python, Good knowledge on Py libraries (Pandas, Numpy, Scikit-learn (ML), Tensorflow/PyTorch),
Exploratory Data Analysis (EDA), Handling large dataset in Amazon S3, Model Training and Optimization, Model deployment, MLOps & Pipeline Automation.
Hands on SageMaker Studio, Training Jobs, Endpoints, Pipeline, Model registry, Feature Store
Hands on AWS Core services (S3, IAM, EC2, Lambda, Cluodwatch)"
Skills: Digital : Python~Digital : Amazon Web Service(AWS) Cloud Computing~Digital : DevOps~Github Enterprise
Experience Required: 10 & Above