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Machine Learning Engineer resume keywords

Core keywords are the skill list on the Machine Learning Engineer resume example. Supporting keywords are skills-catalog entries that name this role.

See the matching Machine Learning Engineer resume example. For which applicant tracking systems large employers use, read the State of ATS 2026 report.

Check your Machine Learning Engineer resume

The ATS checker opens with Machine Learning Engineer filled in as the target role, along with the keyword list on this page. Paste your resume there. Free, no signup.

Counted on 2026-10-10 from 246 public job postings whose titles match Machine Learning Engineer. Those postings came from Ashby, Greenhouse, Lever, and SmartRecruiters. A posting is counted for this role when the longest published job-title phrase in its title is Machine Learning Engineer. The crawl queried Greenhouse, Lever, Ashby, and SmartRecruiters for 133 employers in the State of ATS 2026 dataset that use those vendors, and for 279 additional public boards from the extended coverage tier. The extended boards are not part of the 738-company statistics. 361 boards returned postings out of 412 boards attempted, and 46923 postings were scanned. HTML was stripped before counting, and each posting counts once per term. Phrases beyond the published skill list are the most common two- and three-word phrases in the matched postings. Posting text is not stored. A role page shows these percentages only when at least 30 descriptions were counted.

Core keywords

These are the terms to put on the resume when they match work you have done.

  • Python

    73% of 246 recent postings mention Python.

  • TensorFlow

    32% of 246 recent postings mention TensorFlow.

  • PyTorch

    49% of 246 recent postings mention PyTorch.

  • MLOps

    10% of 246 recent postings mention MLOps.

  • Docker

    5% of 246 recent postings mention Docker.

  • AWS SageMaker

    2% of 246 recent postings mention AWS SageMaker.

  • Feature Engineering

    14% of 246 recent postings mention Feature Engineering.

  • Model Deployment

    4% of 246 recent postings mention Model Deployment.

  • Kubernetes

    16% of 246 recent postings mention Kubernetes.

  • CI/CD

    14% of 246 recent postings mention CI/CD.

Supporting keywords
Phrases from recent postings

These phrases showed up often in the matched postings and are not already on the published skill list.

  • machine learning engineer

    55% of 246 recent postings mention machine learning engineer.

  • computer science

    44% of 246 recent postings mention computer science.

  • large scale

    43% of 246 recent postings mention large scale.

  • real time

    38% of 246 recent postings mention real time.

  • track record

    35% of 246 recent postings mention track record.

  • time off

    33% of 246 recent postings mention time off.

  • cross functional

    33% of 246 recent postings mention cross functional.

  • medical dental

    31% of 246 recent postings mention medical dental.

  • software engineering

    29% of 246 recent postings mention software engineering.

Where to place them

  1. 1

    Headline

    Put the target title and two core terms on the line under your name: Machine Learning Engineer | Python | TensorFlow.

  2. 2

    Skills

    List the core terms together in the skills section: Python, TensorFlow, PyTorch, MLOps, Docker, AWS SageMaker, Feature Engineering, Model Deployment, Kubernetes, CI/CD.

  3. 3

    Experience

    Use Python, TensorFlow, PyTorch inside bullets for work you did in this role, next to the result.

  4. 4

    Supporting terms

    Add these in the skills section or a bullet when you have used them: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Databricks, Dataiku DSS.

Sample lines from the resume example

These lines are already published on the Machine Learning Engineer resume example. Use them as a pattern for where a keyword sits next to a result, and replace the details with your own.

  • Deployed 15+ ML models to production serving 10M+ predictions daily with <50ms latency
  • Built end-to-end MLOps pipeline reducing model deployment time from weeks to hours
  • Improved recommendation model accuracy by 25% generating $5M+ additional annual revenue
  • Designed feature store serving 100+ features to 8 ML teams across the organization

Questions about Machine Learning Engineer keywords

What keywords should a Machine Learning Engineer resume include?

Core keywords for a Machine Learning Engineer resume are Python, TensorFlow, PyTorch, MLOps, Docker, AWS SageMaker, Feature Engineering, Model Deployment, Kubernetes, CI/CD. Core keywords are the skill list on the Machine Learning Engineer resume example. Supporting keywords are skills-catalog entries that name this role. Percentages are the share of 246 public postings fetched on 2026-10-10 whose titles match this role.

Where should Machine Learning Engineer keywords go on a resume?

Headline: Put the target title and two core terms on the line under your name: Machine Learning Engineer | Python | TensorFlow. Skills: List the core terms together in the skills section: Python, TensorFlow, PyTorch, MLOps, Docker, AWS SageMaker, Feature Engineering, Model Deployment, Kubernetes, CI/CD. Experience: Use Python, TensorFlow, PyTorch inside bullets for work you did in this role, next to the result. Supporting terms: Add these in the skills section or a bullet when you have used them: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Databricks, Dataiku DSS.

How do I check a Machine Learning Engineer resume?

Open the free ATS checker with Machine Learning Engineer prefilled, paste your resume, and compare it with the keyword list on this page.

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