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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

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

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

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How much do aws sagemaker jobs pay per hour?

As of Aug 14, 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 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.

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 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.

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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 72% Full Time, 5% Part Time, 2% Temporary, and 21% Contract. Highlights an 81% In-person, 5% Hybrid, and 14% Remote job distribution, with an average salary of $112,422 per year, or $54 per hour.

Senior AWS Developer

Kanak Elite Services Inc

Saratoga, NC • On-site

Contractor

Re-posted 22 days ago

Job description

Role: SENIOR AWS DEVELOPER

Location: North Carolina Local

Duration – 12+ Months

We have some urgent requirements with at least 10 years’ experience as Senior AWS Developer. This role involves close collaboration with the data modernization teams at ITD and DPH to design, implement, and manage AWS solutions that align with their technical requirements and business objectives.

 

MANDATORY – MUST HAVE:

  • Proficient in using various AWS services towards building enterprise level data lakes
  • Experience in modernizing applications, including refactoring, migration, and cloud-native development.
  • Data Ingestion & storage : S3, Amazon Kinesis Data Streams, Amazon Kinesis Data Firehouse, DMS
  • Data Processing & Transformation: AWS Glue, AWS Lambda, EMR, Athena, Amazon Managed Service for Apache Flink,AWS Step Functions, AWS SageMaker
  • Experience with DevOps practices and automation tools
  • Experience in software development, hands on coding using python scripts or any other object-oriented languages like Java/.net.
  • Experience with Agile/Scrum Framework environments.
  • Experience with data analytics, business intelligence solutions (like Power BI or AWS QuickSight )
  • AWS Certification
 
Feel free to reach out to me on anjali08@kanakits.com