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Aws Sagemaker Jobs (NOW HIRING)

Central Business Solutions

AI Engineer

Hillsboro, OR · On-site

Perform lightweight training with AWS SageMaker, AutoML, and deploy inference endpoints. AWS Engineering: Utilize AWS services (Lambda, API Gateway, S3, DynamoDB, SageMaker, Bedrock) for scalable AI ...

Diverse Lynx

AI Engineer with Python

Plano, TX · On-site

... AWS, SageMaker, Kubernetes, CI/CD) • Database expertise (SQL & NoSQL) • Develop and maintain Python backend services, APIs, and microservices • Integrate machine learning models, neural ...

Percient Inc.

AI/ML Lead

Dallas, TX

AWS, Google Cloud Platform, or Azure. * Hands-on experience with Docker and Kubernetes . * Familiarity with cloud AI services such as Amazon Bedrock, AWS SageMaker, Google Vertex AI . * Strong ...

VHL Technologies

AIML Architect

Charlotte, NC · Hybrid

Strong hands-on experience with AWS SageMaker for architecting, training, tuning, deployment, and pipeline automation of enterprise ML solutions. * Strong knowledge of H2O.ai (Driverless AI or H2O3 ...

Group1001

Staff ML Engineer

Zionsville, IN

Snowflake, Dagster, Coalesce, Palantir and AWS SageMaker. This role is for engineers who are as passionate about infrastructure, deployment, and operationalizing ML as they are about the models ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

Snowflake, Dagster, Coalesce, Palantir and AWS SageMaker. This role is for engineers who are as passionate about infrastructure, deployment, and operationalizing ML as they are about the models ...

Lennar

Lead Machine Learning Engineer - REMOTE

Boston, MA · Remote

$111K - $146K/yr

They are hands-on with AWS SageMaker (including SageMaker Unified Studio), MLflow, Weights & Biases, and the surrounding tooling that makes ML systems reliable in production. You'll partner closely ...

Abidi Group LLC

Senior Business Analyst

Washington, DC · Remote

$45 - $50/hr

The current environment is on Agile Scrum, and the team is using technologies such as Snowflake, AWS Bedrock, and Amazon SageMaker. Core business hours is 9-5 PM EST, hired resource may start from 7 ...

Programmers.io

AI/ML Engineer

Scottsdale, AZ · On-site

Manage and optimize cloud-based ML infrastructure (GCP Vertex AI, AWS SageMaker, or equivalent). Implement CICD pipelines for ML and AI-driven applications. Monitor, troubleshoot, and optimize model ...

CCT

Machine Learning Engineer (AWS)

Tulsa, OK · On-site

Build and maintain reproducible model training workflows on AWS (SageMaker, S3, Glue, etc.), making retraining, rollback, and experimentation routine rather than heroic. * Deploy and operate real ...

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How much do aws sagemaker jobs pay per hour?

As of Jun 9, 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 to thrive in the Aws Sagemaker position, and why are they important?

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 are the main day-to-day responsibilities for someone working with AWS SageMaker?

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 job?

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

Product Manager - AI/ML (Sales & Support Technologies)

Purple Drive Technologies

San Jose, CA • On-site

Full-time

Posted 17 days ago

Job description

Overview:
************LOCAL ONLY-RELOCATION WILL NOT BE CONSIDERED***************
Overview:
We are seeking a highly skilled Product Manager with strong expertise in Sales & Support technologies and a proven track record of driving AI/ML initiatives, including Generative and Agentic AI. The ideal candidate will have hands-on experience in shaping product strategy, collaborating across functions, and delivering scalable AI-powered solutions that elevate customer experience and business growth.
Key Responsibilities:
  • Define and execute product strategy and roadmap for AI-powered Sales & Support solutions.
  • Lead the design, development, and implementation of AI/ML solutions (Generative AI, Agentic AI).
  • Collaborate with engineering, data science, design, and business stakeholders to deliver impactful products.
  • Leverage AI ecosystems (Azure OpenAI, Amazon Bedrock, AWS SageMaker) to build scalable solutions.
  • Analyze customer needs, market trends, and business goals to shape product features and priorities.
  • Measure success through key metrics and continuously iterate to improve performance and adoption.
  • Drive alignment between cross-functional teams, ensuring timely delivery and stakeholder satisfaction.

Qualifications:
  • Bachelor's degree in Computer Science, Engineering, Business, or a related field (MBA preferred).
  • 5+ years of Product Management experience with a focus on Sales & Support technologies.
  • Proven expertise in AI/ML implementation, including Generative AI and Agentic AI.
  • Strong knowledge of AI ecosystems such as Azure OpenAI, Amazon Bedrock, and AWS SageMaker.
  • Excellent analytical, problem-solving, and communication skills.
  • Demonstrated ability to lead cross-functional collaboration and deliver measurable business outcomes.

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