TensorFlow and scikit-learn frequently appear together in AI job postings, with 154 current openings requiring both skills. The most common role for this combination is Research Scientist. Jobs requiring both skills pay up to $235K on average. Below you'll find detailed salary data, hiring companies, and related skill combinations.
TensorFlow and scikit-learn appear together in 154 current AI job postings, most commonly for Research Scientist positions. This combination signals that employers are looking for versatile engineers who can work across multiple layers of the AI stack. Companies hiring for this pair tend to value candidates who can bridge different technical domains rather than specialize in just one.
Top Roles Requiring TensorFlow + scikit-learn
Research Scientist73 jobs
AI/ML Engineer49 jobs
Data Scientist10 jobs
MLOps Engineer8 jobs
LLM Engineer6 jobs
Prompt Engineer5 jobs
Career Impact
Professionals who combine TensorFlow and scikit-learn earn a median salary ceiling of
$235K, compared to $233K for TensorFlow alone and
$240K for scikit-learn alone. This 1% discount
reflects the salary ceiling is roughly equivalent whether you specialize in one skill or combine both, suggesting the market values either path equally.
Top Companies Hiring for TensorFlow + scikit-learn
Based on our analysis of current AI job postings, 154 positions require both TensorFlow and scikit-learn skills. The most common role for this combination is Research Scientist.
Jobs requiring both TensorFlow and scikit-learn pay an average of $149K to $235K based on 137 postings with disclosed compensation.
Jobs requiring both TensorFlow and scikit-learn pay $235K on average (max), compared to $233K for TensorFlow alone and $240K for scikit-learn alone. That represents a 1% discount for having both skills.
The most common roles requiring both TensorFlow and scikit-learn are: Research Scientist, AI/ML Engineer, Data Scientist, MLOps Engineer. These positions typically involve building production AI systems that leverage both technologies.
Data Source: Analysis based on 1,969 AI job postings collected and verified by AI Market Pulse. Data reflects active job listings as of March 2026. Salary figures represent posted compensation ranges and may not include equity, bonuses, or other benefits.
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Methodology
Skill co-occurrence data is derived from 154 job postings that list both TensorFlow and scikit-learn
as required or preferred skills. Salary data includes only postings with disclosed compensation ranges.
Data is updated weekly from major job boards and company career pages.
