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Ml Platform Engineer Jobs (NOW HIRING)

Toyota Motor Sales

Lead AI/ML Platform Engineer

Plano, TX · On-site

$98K - $129K/yr

The Lead AI/ML Platform Engineer will support the Enterprise Platforms team's objective to deliver reliable, secure, and high-performing AI platform capabilities that drive business value at scale.

New

Toyota

Lead AI/ML Platform Engineer

Plano, TX · On-site

$98K - $129K/yr

The Lead AI/ML Platform Engineer will support the Enterprise Platforms team's objective to deliver reliable, secure, and high-performing AI platform capabilities that drive business value at scale.

Interon IT Solutions

MLOps Platform Engineer

Reston, VA · On-site

This role will play a key part in enabling scalable, reliable, and secure ML model development and deployment across our cloud and container platforms. This is a hands-on engineering role requiring ...

Interon IT Solutions

MLOps Platform Engineer

Reston, VA · On-site

This role will play a key part in enabling scalable, reliable, and secure ML model development and deployment across our cloud and container platforms. This is a hands-on engineering role requiring ...

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Ml Platform Engineer information

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How much do ml platform engineer jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for ml platform engineer in the United States is $63.95, according to ZipRecruiter salary data. Most workers in this role earn between $50.48 and $73.80 per hour, depending on experience, location, and employer.

What is an ML Platform Engineer?

ML Platform Engineers are specialized software engineers who design, build, and maintain the infrastructure and tools needed to support the development, deployment, and scaling of machine learning models. They bridge the gap between data science and production engineering by automating model training, monitoring, versioning, and serving. Their work enables data scientists to focus on modeling while ensuring that ML solutions are reliable, reproducible, and scalable in real-world environments.

What is the difference between Ml Platform Engineer vs Data Scientist?

AspectML Platform EngineerData Scientist
Required credentialsBachelor's/Master's in CS, Engineering, or related; experience with cloud platformsBachelor's/Master's in Statistics, Math, or CS; strong programming skills
Work environmentBuilds and maintains ML infrastructure, collaborates with engineering teamsAnalyzes data, develops models, and interprets results
Industry usageTech companies, AI startups, enterprises deploying ML systemsResearch institutions, tech firms, data-driven organizations

ML Platform Engineers focus on developing and maintaining the infrastructure that supports machine learning models, while Data Scientists primarily analyze data and build models. Both roles often collaborate but serve different functions within the AI and data ecosystem.

How does an ML Platform Engineer typically collaborate with data scientists and software engineers within a company?

ML Platform Engineers work closely with both data scientists and software engineers to streamline the process of developing, deploying, and maintaining machine learning models. They provide the infrastructure and tools necessary for data scientists to build and experiment with models efficiently, while ensuring seamless integration with production systems managed by software engineers. Regular communication, participation in cross-functional meetings, and shared project management tools are common ways teams collaborate. This close collaboration helps to bridge the gap between research and production, ensuring robust, scalable, and reliable ML solutions.

What skills and qualifications are needed to thrive as an ML Platform Engineer?

To thrive as an ML Platform Engineer, you need a strong background in computer science, software engineering, and machine learning concepts, often supported by a degree in a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), containerization (Docker, Kubernetes), CI/CD pipelines, and knowledge of ML frameworks (TensorFlow, PyTorch) are commonly required. Collaboration, problem-solving, and strong communication skills help you work efficiently with data scientists, engineers, and stakeholders. These skills ensure the development, scalability, and reliability of robust ML infrastructure that empowers teams to deploy and manage models effectively.
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Ml Platform Engineer jobs near you
Infographic showing various Ml Platform Engineer job openings in the United States as of August 2026, with employment types broken down into 52% Full Time, 44% Part Time, and 4% Contract. Highlights an 78% Physical, 2% Hybrid, and 20% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.

MLOps Platform Engineer (SageMaker)

IVID TEK INC

Plano, TX • On-site

$90 - $95/hr

Contractor

Posted 16 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
IVidTek logo

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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