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Aws Sagemaker Jobs (NOW HIRING)

IVID TEK INC

MLOps Platform Engineer (SageMaker)

Plano, TX · On-site

$90 - $95/hr

... on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML toolchain ... to a unified, governed platform on AWS Landing Zone 2, covering the full ML lifecycle from data ...

IVID TEK INC

MLOps Platform Engineer (SageMaker)

Plano, TX · On-site

$123.98 - $130.87/hr

... on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML toolchain ... to a unified, governed platform on AWS Landing Zone 2, covering the full ML lifecycle from data ...

Value Technology Inc

Aws DevOps Engineer

Dallas, TX · On-site

$52.50 - $71.75/hr

AWS SageMaker Notebooks * AWS Bedrock * Containerized solutions (ECS/EKS) * AWS IAM * AI/ML Ops with SageMaker & Bedrock Education and Experience * 5-7 years of software development experience * NO ...

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How much do aws sagemaker jobs pay per hour?

As of Sep 4, 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.

MLOps Platform Engineer (SageMaker)

IVID TEK INC

Plano, TX • On-site

$90 - $95/hr

Contractor

Re-posted 5 days ago

Job description

Title: MLOps Platform Engineer (SageMaker)
Duration: 12 months with extension
Location: Onsite in Plano, TX 75024
Job ID – 1497588
pay - $90-95/hr W2 (USC/ GC/ H4 / EAD)

What we’re looking for:
Client Enterprise Platforms team is looking for a Senior ML Platform Engineer to design, build, and operationalize an enterprise ML platform on AWS SageMaker Unified Studio. You will migrate the organization from a fragmented ML toolchain to a unified, governed platform on AWS Landing Zone 2, covering the full ML lifecycle from data discovery through model deployment and monitoring.

What you’ll be doing:
  • Set up SageMaker Unified Studio platform — domain configuration, project provisioning, persona-based roles, and multi-environment (Dev, Prod-UAT, Prod) promotion workflows
  • Build MLOps pipelines using SageMaker Pipelines — data extraction from Snowflake, preprocessing, training, evaluation, and model registration
  • Manage SageMaker Model Registry — cross-account model promotion, versioning, immutability, and lineage tracking
  • Configure MLflow experiment tracking — auto-logging of parameters, metrics, and artifacts
  • Set up identity and access management — Okta SSO, SailPoint entitlements, persona-based execution roles, service roles for pipelines
  • Build model serving — real-time SageMaker endpoints and batch prediction workflows
  • Set up model monitoring — data drift, model drift, performance degradation detection
  • Configure data catalog — searchable datasets, access-level visibility, access-request workflows, lineage
  • Own platform operations — observability (CloudWatch, Datadog), logging, custom images, instance availability

Requirements:
Qualifications/ What you bring (Must Haves): – Highlight Top 3-5 skills
  • 10-15 years of software engineering experience focused on cloud infrastructure or ML platform operations
  • 5+ years hands-on with AWS, including deep expertise in Amazon SageMaker (Studio, Pipelines, Model Registry, Endpoints, Feature Store)
  • 3+ years building and operating production MLOps pipelines — training, versioning, deployment, monitoring, rollback
  • Experience with SageMaker Unified Studio or Studio Classic — domain/project setup, blueprints, multi-tenant configuration
  • Infrastructure-as-Code with Terraform, CDK, or CloudFormation
  • IAM design for ML platforms — execution roles, service roles, cross-account access, Lake Formation, SSO/SAML
  • MLflow or equivalent experiment tracking
  • SageMaker Pipelines or similar workflow orchestration (Airflow, Step Functions)
  • Model serving — real-time endpoints, batch transform, auto-scaling, endpoint monitoring
  • Snowflake as a data source for ML pipelines
  • Kubernetes (EKS) and container orchestration
  • Networking and security — VPC, security groups, private endpoints, cross-account connectivity

Added bonus if you have (Preferred):
  • SageMaker Unified Studio domain provisioning, custom blueprints, project standardization
  • SageMaker Feature Store for online/offline feature management
  • SageMaker Model Monitor — data quality checks, bias detection, drift detection
  • AWS Machine Learning Specialty certification

Interview Process:
1st Round- MS Teams - Technical Interview – SageMaker and AWS
2nd Round- MS Teams - Technical Interview – SageMaker and AWS
harsha@ividtek.com
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About IVidTek

Sourced by ZipRecruiter

We are a group of tech enthusiasts working with some of the best technologies and organizations around the world. We transform businesses into digital entities seamlessly and also provide IT consulting and support services.

Industry

It services

Company size

1 - 10 Employees

Headquarters location

Lake Saint Louis, MO, US

Year founded

2016

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