Machine Learning Engineer skills · 42 job postings analysed
Machine Learning Engineer skills required in 2026
We analysed 42 machine learning engineer job postings from 21 companies (India, August 2026 – September 2026). The most requested skill is Python, mentioned by 85% of hiring companies, followed by AWS, LLMs and PyTorch. Postings that state experience ask for a median of 5 years.
- 1. Python85% of companies
- 2. AWS65% of companies
- 3. LLMs60% of companies
- 4. PyTorch55% of companies
- 5. TensorFlow50% of companies
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From real job postings
Full machine learning engineer skills breakdown
Share of hiring companies asking for each skill
- Python85%
- AWS65%
- LLMs60%
- PyTorch55%
- TensorFlow50%
- Kubernetes50%
- Docker45%
- SQL40%
- CI/CD40%
- Generative AI35%
- Scikit-learn30%
- Azure30%
Soft skills mentioned
- Communication10%
- Problem solving10%
Education mentioned
- Master's / MBA76%
- Bachelor's degree57%
- B.Tech / B.E.33%
Of postings that state an education requirement.
Median experience asked
5 yrs
0% open to 0–1 years
Work mode
60% office
Office 60% · Hybrid 2% · Remote 22%
Postings analysed
42
21 companies · India
Top Indian cities
Bengaluru
Hyderabad · Pune · Noida
Companies in this sample include Warner Bros. Discovery, The Nielsen Company, Hewlett Packard Enterprise | HPE, Level AI, Weekday, Smartsheet, Gradera Inc., Riveron.
Method: postings collected by the Resumaxx job catalog (August 2026 – September 2026). Skill shares count each company once, so one employer posting many similar jobs doesn't skew the list. Figures describe this sample, not the whole market.
Before you apply
How to tailor your machine learning engineer resume
Usually required
Most companies that mention these list them as requirements. If you have them, make them easy to find.
- Python
- AWS
- LLMs
- PyTorch
- TensorFlow
Common differentiators
Frequently mentioned, often as a preference rather than a must.
- Kubernetes
- Docker
- SQL
- CI/CD
- Generative AI
Industries hiring in this sample: AI/ML, Consumer, Media, Software Development, Machine Learning, Technology, Information and Internet.
What makes a data resume match
- Lead with the tools the posting names (SQL, Python, BI tool, cloud) and show each one in a real project.
- Tie every model or dashboard to a decision or metric it changed, not just its accuracy.
- Separate production work from coursework or Kaggle so seniority is clear.
How the match works
- 1. We read the job description and list its requirements, marking each as required or preferred.
- 2. We look for each requirement in your resume and quote the line that proves it.
- 3. A match only counts if the quote is really in your resume. Required skills count double.
Frequently asked questions
What skills do machine learning engineer job descriptions ask for?
In the 42 postings we analysed, the most common were Python (85% of companies), AWS (65% of companies), LLMs (60% of companies), PyTorch (55% of companies), TensorFlow (50% of companies). Match these against the specific job description you are applying to, because each employer weights them differently.
How much experience do machine learning engineer jobs require?
Postings that state a minimum ask for a median of 5 years. 0% accept a year or less, and 58% ask for five years or more (based on 33 postings that stated a number).
Are machine learning engineer jobs remote or in office?
Of postings that specified it, 60% were office-based, 2% hybrid, and 22% remote.
How does the job description match score work?
We pull the requirements out of the job description you paste, mark each one as required or preferred, and look for evidence of it in your resume. Only quotes that actually appear in your resume count as a match. The score is weighted so required skills count twice as much as preferred ones.
Should I add every missing keyword to my resume?
No. Add a skill only if you have genuinely used it, and show it inside a bullet about real work rather than only in a skills list. Recruiters and screening tools both treat unsupported keywords as padding.