AI Platform Engineer Jobs

AI Platform Engineer jobs are open across cloud services, financial services, healthcare technology, and enterprise software, from new-grad to principal and staff levels, with specializations in MLOps, LLM infrastructure, and data pipeline architecture. Find a role that fits from the openings below and apply directly.

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Overview

Open roles237+
Top stateCalifornia
Top employerBoston Consulting
Top citySan Francisco, CA
Work type62% On-site
Top industryTechnology

Showing 5 of 237+ AI Platform Engineer jobs

Hi Marley
Principal AI Platform Engineer
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Hi Marley
Added 1d ago
Principal AI Platform Engineer
Hi Marley
Boston, Massachusetts
Cloud & DevOps
Software Engineering
Technical Product & Program Management
Cloud Engineering
AI (Artificial Intelligence)
DevOps
$152k - $283k/yr
Hybrid
None
11-50

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McAfee
Senior AI Platform Engineer
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McAfee
Added 4d ago
Senior AI Platform Engineer
McAfee
Frisco, Texas
Software Engineering
Cloud & DevOps
Data Science & Analytics
AI (Artificial Intelligence)
Cloud Engineering
DevOps
Data Science
$107k - $176k/yr
Hybrid
None
1,001-5,000

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Novartis
Director, AI Platform Engineer
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Novartis
Added 5d ago
Director, AI Platform Engineer
Novartis
Remote
Software Engineering
Technical Product & Program Management
Data Science & Analytics
Cloud & DevOps
AI (Artificial Intelligence)
Technical Program Management
$195k - $361k/yr
Remote (US)
Bachelor's
10,000+

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NVIDIA
Senior Staff AI Platform Engineer
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NVIDIA
Added 1w ago
Senior Staff AI Platform Engineer
NVIDIA
Santa Clara, California
Software Engineering
Cloud & DevOps
AI (Artificial Intelligence)
ML (Machine Learning)
Cloud Engineering
DevOps
$168k - $322k/yr
On-Site
Bachelor's

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Twin Health
Senior AI Platform Engineer
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Twin Health
Added 1w ago
Senior AI Platform Engineer
Twin Health
United States
Software Engineering
Data Science & Analytics
Technical Product & Program Management
AI (Artificial Intelligence)
ML (Machine Learning)
Technical Program Management
$180k - $200k
On-Site
Bachelor's

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AI Platform Engineer Job Market

A snapshot from current openings nationwide, updated as new roles post.

Who's Hiring

  • Boston Consulting
    Boston Consulting10
  • Apple
    Apple7
  • Adobe
    Adobe6
  • Databricks
    Databricks5
  • Together AI
    Together AI5

Top Industries Hiring

  • Technology & Software124
  • Consulting & Professional Services25
  • Electronics & Hardware23
  • Artificial Intelligence15
  • Investment & Asset Management11

What Employers Look For

The qualifications that appear most often in AI platform engineer jobs.

  • Proficiency in Python and at least one infrastructure-as-code tool such as Terraform
  • Hands-on experience with Kubernetes, Docker, and container orchestration at scale
  • Experience building or maintaining MLOps pipelines using tools like Kubeflow, MLflow, or similar
  • Familiarity with major cloud platforms including AWS, Google Cloud, or Microsoft Azure
  • Bachelor's degree in computer science, engineering, or a related technical field
  • Experience with data pipeline frameworks such as Apache Spark, Airflow, or Ray

Tips for Your AI Platform Engineer Job Search

Quantify your model serving infrastructure

Hiring managers for ai platform engineer roles want to see scale, not just tools. Rewrite your resume bullets to show request throughput, latency improvements, or cost reductions you delivered when deploying or maintaining model serving systems.

Distinguish MLOps from platform engineering clearly

Many ai platform engineer postings blur the line between MLOps tooling and core infrastructure work. Read each job description carefully and mirror its language in your application so your background maps to what that specific team actually builds.

Apply early to roles that fit

Migrate Mate lists ai platform engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.

Build a portfolio around reproducible pipelines

A GitHub repository showing a working feature store, model registry, or CI/CD pipeline for ML models signals practical ability faster than certifications alone. Interviewers for this role consistently probe whether you can design reproducible, observable systems.

Prepare for system design rounds on ML infrastructure

AI platform interviews almost always include a distributed systems or ML infrastructure design round. Practice designing low-latency inference pipelines, batch training orchestration, and data versioning systems out loud so you can communicate tradeoffs clearly under time pressure.

Negotiate scope before you negotiate salary

When you reach the offer stage, clarify whether the role owns the platform roadmap or supports a separate ML engineering team. The distinction shapes your career trajectory, and it gives you a more informed foundation for any compensation conversation that follows.

AI Platform Engineer Jobs: Frequently Asked Questions

Which companies are hiring the most ai platform engineers?

The companies hiring the most ai platform engineers right now include Boston Consulting, Apple, and Adobe, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of June 2026. Demand is concentrated at organizations running large-scale model deployment programs across cloud, financial services, and enterprise software.

How many ai platform engineer jobs are remote?

About 38% of ai platform engineer openings are fully remote or hybrid as of June 2026, making it one of the more distributed engineering specializations. Roles focused on MLOps tooling, pipeline automation, and infrastructure-as-code tend to be the most remote-compatible, while positions tied to on-premise GPU clusters or regulated data environments are more likely to require on-site presence.

How do you become an ai platform engineer?

Start by building a strong foundation in software engineering and distributed systems, then layer in cloud infrastructure skills on at least one major provider. Learn containerization with Docker and Kubernetes, then move into ML-specific tooling by deploying a real model using an open-source pipeline framework. Contributing to open-source MLOps projects or maintaining a public portfolio of reproducible pipelines accelerates hiring consideration significantly.

Can you get an ai platform engineer job with little experience?

Entry-level ai platform engineer roles do exist, particularly at companies that treat the position as a specialized infrastructure role rather than a senior-only function. Candidates with strong DevOps or backend engineering backgrounds who have independently built and deployed a machine learning pipeline, even on a personal or open-source project, are competitive for these positions without prior professional ML infrastructure experience.

What does the ai platform engineer interview process look like?

The process typically begins with a recruiter screen focused on your infrastructure background, followed by a technical phone interview covering Python, distributed systems, or cloud architecture. Later rounds usually include a system design interview centered on ML pipeline or model serving architecture, a coding round emphasizing data structures and automation, and a final loop with engineering managers or platform leads assessing cross-functional collaboration.

Where can I find and apply to ai platform engineer jobs?

You can find and apply to ai platform engineer jobs on Migrate Mate, which lists current openings from employers across the United States. Find roles that match your background and apply directly to each listing.

See All 237+ AI Platform Engineer Jobs

Jump back to the full list of openings and apply to any AI platform engineer role that fits.

Find AI Platform Engineer Jobs