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Aws Sagemaker Jobs (NOW HIRING)

Diverse CG Sp. z o.o. Sp.k.

NY · On-site

$90 - $140/hr

Business Analyst (ML & AWS SageMaker) As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to ...

DCG Poland

NY · On-site

$90 - $150/hr

Business Analyst (ML & AWS SageMaker) As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to ...

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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.

Business Analyst (ML & AWS SageMaker) AWS SageMaker, CI/CD, Big Data, SQL, Python Warszawa, Łód[...]

Diverse CG Sp. z o.o. Sp.k.

NY • On-site

$90 - $140/hr

Other

Posted 16 days ago

Job description

Position: Business Analyst (ML & AWS SageMaker)

As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for:

Business Analyst (ML & AWS SageMaker)

Responsibilities:

  • Act as a bridge between business stakeholders and development teams to translate business needs into functional and non-functional requirements
  • Support the design of advanced data and analytics solutions
  • Collaborate with stakeholders to understand expected outcomes and elicit business features
  • Manage delivery dependencies across teams and organizational units
  • Participate as a member of a cross-functional Agile delivery team
  • Analyze complex end-to-end solutions and business processes
  • Evaluate new technologies at a high level and identify key technical questions
  • Communicate effectively with business users and stakeholders

Requirements:

  • Hands-on experience in AWS SageMaker implementation in direct collaboration with data scientists as end users
  • Strong communication skills and ability to work with business stakeholders
  • Analytical thinking and problem-solving skills
  • Familiarity with machine learning concepts, CI/CD pipelines and big data
  • Knowledge of SQL and Python

Nice to have:

  • Experience in implementation of model monitoring and MLOps capabilities
  • Experience integrating AWS SageMaker model outputs with cloud, hybrid and on-premises solutions
  • Advanced knowledge of machine learning algorithms
  • Knowledge of Spark and Scala

Offer:

  • Private medical care
  • Co‑financing for the sports card
  • Constant support of dedicated consultant

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