What recruiters should know
TensorFlow is noted in 34% of ML engineer job postings and remains the dominant production ML framework for enterprise deployment (365 Data Science 2026). Keras (now a standalone multi-backend library) reduces the learning curve. TensorFlow's production-grade serving infrastructure (TF Serving, TFX) makes it preferred for enterprise AI systems. PyTorch has surpassed TensorFlow in research adoption but TensorFlow leads in production deployment, especially at Google, Airbnb, Twitter, and large enterprises.
In plain terms
Open-source machine learning framework for training and deploying ML models
Industry demand
Overall level
very high
Trend
stable dominant
Top hiring sectors
- Enterprise AI
- Healthcare AI
- Financial Services ML
- Manufacturing AI
- Autonomous Systems
Proficiency ladder
What each level looks like in the work — behavioural markers, not job titles.
At this level, a developer can…
- Basic models
- Keras API
- Simple neural nets
- Training basics