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Aws Sagemaker Remote Jobs (NOW HIRING)

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

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 ...

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 ...

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Aws Sagemaker Remote information

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How much do aws sagemaker remote jobs pay per hour?

As of Aug 14, 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?

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.
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What cities are hiring for Aws Sagemaker Remote jobs?

Cities with the most Aws Sagemaker Remote job openings:

What are the most commonly searched types of Aws Sagemaker jobs?

The most popular types of Aws Sagemaker jobs are:

What states have the most Aws Sagemaker Remote jobs?

States with the most job openings for Aws Sagemaker Remote jobs include:

Infographic showing various Aws Sagemaker Remote job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 1% Part Time, and 10% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $112,422 per year, or $54 per hour.

Data Scientist II

Corvel

Irvine, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


CorVel rating

7.9

Company rating: 7.9 out of 10

Based on 51 frontline employees who took The Breakroom Quiz

85th of 150 rated financial services


Job description

We have an exciting opportunity for a Data Scientist within our data product space. This individual will be focused on designing, building, and deploying machine learning models and data products that support our enterprise initiatives. This role focuses on developing scalable, production ready solutions by translating complex business problems into data-driven approaches and model-based outputs.

Working closely with product managers, engineering teams, and business stakeholders, this position contributes to the development of data products from concept through deployment, ensuring solutions are reliable, performant, and aligned with real world use cases. The role includes hands on model development, feature engineering, and integration into production systems within cloud environments.

The ideal candidate has experience building and operationalizing machine learning models and is comfortable working with modern AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), where applicable. Experience with platforms such as Azure, AWS, or similar ecosystems is strongly preferred.

Success in this role requires strong technical expertise, problem-solving skills, and the ability to deliver high-quality solutions within a structured development environment. This role focuses on building and deployment of production data products and is not limited to exploratory analysis or reporting.

This position is open to remote or hybrid.

ESSENTIAL FUNCTIONS & RESPONSIBILITIES:

  • Mine and analyze data from internal databases to drive optimization and improvement of product development and business strategies
  • Creating new, experimental frameworks to collect data
  • Building tools to automate data collection
  • Develop custom data models and algorithms to apply to data sets
  • Design, build, train, and deploy machine learning models and data products for enterprise use
  • Translate business and operational needs into scalable data science solutions and modeling approaches
  • Perform feature engineering, data preparation, and exploratory analysis to support model development
  • Develop and evaluate models using appropriate techniques (e.g., classification, regression, NLP, optimization)
  • Contribute to the design of data products, including model outputs, APIs, and integration into downstream systems
  • Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate
  • Collaborate with engineering teams to integrate models into production environments using APIs, pipelines, and cloud services
  • Support deployment and lifecycle management of models within Azure Machine Learning, AWS, or similar platforms
  • Perform model validation, testing, and documentation to ensure quality and reproducibility
  • Contribute to technical design discussions and provide input on architecture and implementation strategies
  • Work within the full software development lifecycle (SDLC), including version control, testing, and release processes
  • Communicate model behavior, assumptions, and results clearly to technical and non-technical stakeholders
  • Develop A/B testing framework and test model quality
  • Passion for technology and emerging AI/ML trends
  • Additional duties as assigned

KNOWLEDGE & SKILLS:

  • Strong problem-solving skills with an emphasis on product development.
  • Strong foundation in machine learning, statistical modeling, and data science techniques
  • Experience building and deploying machine learning models in production environments
  • Familiarity with modern AI approaches, including:
    • Natural language processing (NLP)
    • Large language models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • Feature engineering and model evaluation techniques
  • Experience working with cloud platforms such as Azure, AWS, or similar ecosystems
  • Familiarity with data pipelines, APIs, and integration patterns
  • Proficiency in programming languages such as Python and database management including SQL
  • Strong problem-solving skills with the ability to structure complex problems into analytical solutions
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), their real-world advantages/drawbacks and experience with applications
  • Excellent presentation and written/verbal communication skills

EDUCATION & EXPERIENCE:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master’s preferred
  • 2–5+ years of experience in data science, machine learning, or related roles
  • Experience developing and deploying machine learning models in production environments
  • Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar
  • Exposure to AI platforms such as Azure OpenAI, AWS Bedrock, or similar technologies preferred
  • Experience working within enterprise software environments and SDLC practices preferred

PAY RANGE:

CorVel uses a market based approach to pay and our salary ranges may vary depending on your location.  Pay rates are established taking into account the following factors:  federal, state, and local minimum wage requirements, the geographic location differential, job-related skills, experience, qualifications, internal employee equity, and market conditions.  Our ranges may be modified at any time.

For leveled roles (I, II, III, Senior, Lead, etc.) new hires may be slotted into a different level, either up or down, based on assessment during interview process taking into consideration experience, qualifications, and overall fit for the role.  The level may impact the salary range and these adjustments would be clarified during the offer process.

Pay Range:  $82,574 – $127,490

A list of our benefit offerings can be found on our CorVel website: CorVel Careers | Opportunities in Risk Management

In general, our opportunities will be posted for up to 1 year from date of posting, or until we have selected candidate(s) to fulfill the opening, whichever comes first.

About CorVel

CorVel, a certified Great Place to Work® Company, is a national provider of industry-leading risk management solutions for the workers’ compensation, auto, health and disability management industries.   CorVel was founded in 1987 and has been publicly traded on the NASDAQ stock exchange since 1991. Our continual investment in human capital and technology enable us to deliver the most innovative and integrated solutions to our clients.  We are a stable and growing company with a strong, supportive culture and plenty of career advancement opportunities.  Over 4,000 people working across the United States embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).

A comprehensive benefits package is available for full-time regular employees and includes Medical (HDHP) w/Pharmacy, Dental, Vision, Long Term Disability, Health Savings Account, Flexible Spending Account Options, Life Insurance, Accident Insurance, Critical Illness Insurance, Pre-paid Legal Insurance, Parking and Transit FSA accounts, 401K, ROTH 401K, and paid time off.

CorVel is an Equal Opportunity Employer, drug free workplace, and complies with ADA regulations as applicable.

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