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Aws Sagemaker Remote Jobs (NOW HIRING)

Corvel

Data Scientist II

Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar ... Remote

SAIC

AI Data Engineer

Fort Belvoir, VA · On-site +1

$120K - $160K/yr

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking an AI Data ... Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, AWS SageMaker)

Omada Health

Senior Applied AI Engineer

$107K - $146K/yr

Expertise in machine learning tools (e.g., AWS SageMaker, PyTorch, Hugging Face) * General ... Remote first work from home culture * Flexible Time Off to help you rest, recharge, and connect ...

Corvel

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar ... Remote Equal Opportunity Employer This employer is required to notify all applicants of their ...

Ibotta

Principal Machine Learning Engineer

Denver, CO · On-site +1

$228K - $253K/yr

... Databricks, AWS, Sagemaker, etc. As a Principal Machine Learning Engineer, you will act as a ... Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA ...

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

... technologies (e.g., AWS Sagemaker) Strong experience with machine learning environments (e.g ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

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How much do aws sagemaker remote jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for aws sagemaker remote 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 some common challenges faced by AWS SageMaker professionals working remotely, and how can they be addressed?

Remote AWS SageMaker professionals often encounter challenges such as managing secure access to sensitive data, collaborating effectively with distributed teams, and ensuring consistent deployment environments. To address these, it's important to leverage AWS security best practices, use version control and documentation tools, and participate in regular virtual meetings to stay aligned with team members. Additionally, taking advantage of AWS’s integrated collaboration features and establishing clear communication protocols can help mitigate these obstacles and ensure project success.

What is an AWS SageMaker remote job?

An AWS SageMaker remote job typically refers to a position where professionals use Amazon SageMaker, a cloud-based machine learning platform, to develop, train, and deploy machine learning models while working remotely. These roles often involve collaborating with teams via online tools, performing data analysis, and building models using SageMaker's suite of features without having to be physically present in an office. This allows for flexibility and access to global talent, as all work can be conducted over the internet while leveraging AWS infrastructure.

What is the difference between Aws Sagemaker Remote vs Data Scientist?

AspectAws Sagemaker RemoteData Scientist
Required CredentialsAWS certifications, cloud computing skillsStatistics, data analysis, programming (Python/R)
Work EnvironmentCloud platforms, remote or on-premiseOffice, remote, or hybrid
Industry UsageMachine learning deployment, cloud servicesData analysis, modeling, research

While Aws Sagemaker Remote focuses on deploying and managing machine learning models on AWS cloud, Data Scientists primarily analyze data, build models, and generate insights. Both roles require technical skills, but Sagemaker Remote emphasizes cloud infrastructure and deployment, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as an AWS SageMaker Remote Specialist, and why are they important?

To thrive as an AWS SageMaker Remote Specialist, you need expertise in machine learning, data science, cloud computing, and a strong understanding of AWS services, often supported by a degree in computer science or a related field. Familiarity with tools like Jupyter Notebooks, Python, TensorFlow, and official AWS certifications such as AWS Certified Machine Learning – Specialty are typically required. Excellent problem-solving, teamwork, and communication skills help you collaborate with distributed teams and translate business needs into technical solutions. These competencies are crucial for efficiently building, deploying, and managing scalable machine learning models in a remote cloud environment.
More about Aws Sagemaker Remote jobs
What cities are hiring for Aws Sagemaker Remote jobs? Cities with the most Aws Sagemaker Remote job openings:
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Aws Sagemaker Remote jobs near you
Infographic showing various Aws Sagemaker Remote job openings in the United States as of June 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% Remote job distribution, with an average salary of $112,422 per year, or $54 per hour.
AI Architect (with Azure)-Remote : Contract on w2

AI Architect (with Azure)-Remote : Contract on w2

Marvel Technologies Inc

Southfield, MI • Remote

$65 - $84.75/hr

Contractor

Posted 9 days ago

Job description

Job Title :  AI Architect (with Azure)

Location :   Remote-USA

Duration : Long Term Contract

Contract on w2

Domain- Preferred Insurance.

Experience: 15+ years

Role Overview:

We are seeking a highly skilled AI Azure Architect to lead the architecture and technical strategy for AI programs across insurance and other regulated industries. The AI Architect will own and define reference architectures for Retrieval-Augmented Generation (RAG), Conversational AI, Document Intelligence, and Agentic AI, ensuring solutions are scalable, secure, compliant, and deliver measurable business value on AWS cloud/Azure Cloud.

Key Responsibilities:

  • Define end-to-end AI architectures covering ingestion → storage → retrieval → reasoning → action → monitoring.
  • Own and evolve reference architectures for Document AI, Conversational AI, and Agentic AI.
  • Specify non-functional requirements (latency, throughput, privacy, compliance, observability, cost).
  • Select and justify AWS-native AI/ML services (Bedrock, SageMaker, Kendra, OpenSearch, etc.) and third-party tools.

OR

  • Select and justify Azure-native AI/ML Services - Azure AI Foundry, Azure SDK, Cosmos DB, Azure OpenAI, Azure Blob Storage, Azure AI Search, Azure Cognitive Services, Service Principals, and Azure Agent (critical for agentic workflows).
  • Govern prompt/version management, enforce safety policies, and manage controls for prompt injection and PII protection.
  • Lead PoCs to production with AWS-based templates and golden paths.
  • Collaborate with stakeholders; mentor engineers; conduct design/code reviews.
  • Establish measurement frameworks (hallucination rate, groundedness, answer quality, CSAT, deflection).
  • Ensure seamless AWS/Azure enterprise integrations with insurance platforms (policy, claims, underwriting).

Required Skills & Experience:

  • 15+ years in AI/ML software, 3–5+ years in solution/enterprise architecture.
  • Proven experience designing AI systems at enterprise scale on AWS/Azure.
  • Hands-on with AWS Bedrock, SageMaker, Lambda, Kendra, OpenSearch, Redshift, DynamoDB, S3.

OR

  • Hands on Azure AI Foundry, Azure SDK, Cosmos DB, Azure OpenAI, Service Principals, Azure Blob, Azure AI Search, Azure Cognitive Services, and Azure Agent.
  • Expertise in LLMs, vector databases, RAG pipelines, and agentic workflows.
  • Strong multi-cloud cost/latency tradeoff knowledge.
  • Excellent communication, stakeholder engagement, and blueprinting skills.
  • Insurance industry experience strongly preferred (FNOL, claims adjudication, underwriting, billing, policy servicing).