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Aws Sagemaker Machine Learning Remote Jobs (NOW HIRING)

Accompany Health

Senior Machine Learning Engineer

$175K - $200K/yr

... remote team to solve novel problems at the intersection of AI and compassionate care delivery ... AWS Sagemaker or Bedrock is preferred) * Healthcare experience is valuable but not required You ...

Chewy

Senior Machine Learning Engineer

Bellevue, WA · On-site +1

$149K - $245K/yr

Machine learning and deep-learning models will influence selection, relevance, ranking, click ... Experience with ML Services in AWS (SageMaker, Personalize) or equivalent. The base salary range ...

Palnar

Salesforce Developer@ Remote Role

$56.75 - $75.25/hr

Build and optimize end-to-end machine learning pipelines using tools like Docker, AWS Sagemaker, and Airflow. Work on delivering solutions that improve KPIs or business outcomes. Apex Development:

Chewy

Senior Machine Learning Engineer

Boston, MA · On-site +1

$149K - $245K/yr

Machine learning and deep-learning models will influence selection, relevance, ranking, click ... Experience with ML Services in AWS (SageMaker, Personalize) or equivalent. The base salary range ...

Corvel

Data Scientist II

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

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 ...

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How much do aws sagemaker machine learning remote jobs pay per year?

As of Jun 8, 2026, the average yearly pay for aws sagemaker machine learning remote in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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

AspectAws Sagemaker Machine Learning RemoteData Scientist
Required CredentialsAWS certifications, machine learning knowledgeStatistics, data analysis, programming skills
Work EnvironmentRemote, cloud-based platformsOffice or remote, research and analysis focus
Industry UsageTech, cloud services, AI projectsFinance, healthcare, marketing, research
Common Search/ComparisonYesYes

While Aws Sagemaker Machine Learning Remote specialists focus on deploying and managing ML models on AWS cloud, Data Scientists analyze data to generate insights and develop models. Both roles require technical skills, but differ in their primary focus and work environment.

What is an AWS SageMaker Machine Learning Remote job?

An AWS SageMaker Machine Learning Remote job involves working with Amazon SageMaker, a cloud-based machine learning platform, to build, train, and deploy machine learning models, all while working remotely. Professionals in this role use SageMaker’s tools and services to handle data preprocessing, model development, and model deployment at scale. They collaborate with data scientists, engineers, and stakeholders, all through remote communication tools, making it possible to work from anywhere. This job typically requires knowledge of Python, machine learning frameworks, and experience with AWS cloud services.

What are some common challenges faced by AWS SageMaker Machine Learning engineers working remotely, and how can they be addressed?

One common challenge for AWS SageMaker Machine Learning engineers working remotely is ensuring seamless collaboration with cross-functional teams, such as data engineers, DevOps, and stakeholders, due to the distributed work environment. Effective communication tools, regular virtual meetings, and clear documentation can help bridge gaps and prevent misunderstandings. Additionally, managing cloud resources and costs remotely requires diligent monitoring and adherence to best practices. Staying updated on AWS SageMaker releases and participating in online knowledge-sharing sessions also helps maintain productivity and innovation.

What are the key skills and qualifications needed to thrive as an AWS SageMaker Machine Learning Engineer working remotely, and why are they important?

To thrive as an AWS SageMaker Machine Learning Engineer, you need a strong background in machine learning algorithms, Python programming, and experience with cloud-based deployment, typically supported by a degree in computer science or related field. Familiarity with AWS SageMaker, cloud infrastructure (like EC2, S3), and relevant certifications such as AWS Certified Machine Learning – Specialty are highly valuable. Strong problem-solving, communication, and self-motivation are crucial soft skills for effective remote collaboration and project delivery. These competencies ensure the ability to build, deploy, and maintain scalable machine learning solutions while working efficiently in distributed teams.
Infographic showing various Aws Sagemaker Machine Learning Remote job openings in the United States as of May 2026, with employment types broken down into 9% Locum Tenens, 5% Internship, 58% As Needed, 14% Full Time, 9% Temporary, and 5% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Principal Machine Learning Data Scientist, Gen AI

Principal Machine Learning Data Scientist, Gen AI

Xometry

Remote

Full-time

Posted 12 days ago

Job description

Job Summary:
Xometry is a company that connects innovative ideas with manufacturers to enhance their business. They are seeking a Principal Data & ML Scientist to lead the Generative AI team, focusing on advancing machine learning and generative AI capabilities to develop innovative AI-driven solutions.
Responsibilities:
• Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development.
• Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry’s business objectives.
• Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents.
• Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models.
• Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models.
• Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment.
• Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications.
• Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team’s technical capabilities.
• Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment.
• Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development.
Qualifications:
Required:
• A bachelor’s degree is required.
• 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision.
• Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs).
• Experience with multimodal data processing (e.g., combining text, image, and 3D data).
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
Preferred:
• An advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• Experience in the manufacturing, supply chain, or similar industries is a plus.
Company:
Xometry is an online marketplace that allows customers to access a network of machine shops and custom manufacturers. Founded in 2013, the company is headquartered in Gaithersburg, USA, with a team of 1001-5000 employees. The company is currently Late Stage.
Xometry logo

About Xometry

Sourced by ZipRecruiter

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Industry

Software development

Company size

501 - 1,000 Employees

Headquarters location

Gaithersburg, MD, US

Year founded

2013

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