AI and ML
Job Market Intelligence
Which AI skills are employers actually hiring for? Rankings for ML engineering, LLM development and AI operations — built from active job postings, not surveys, updated weekly.
Skills snapshot: 2026-06-02 · Updated weekly
Active AI listings
1,168
Live job postings
Top skill
Machine Learning
36% of AI listings
Top role
ML Engineer
447 open positions
Data cadence
Weekly
Snapshots from job postings
Top AI and ML skills by demand
Snapshot: 2026-06-02
Machine Learning
LLMs / GenAI
Scala
AWS
Python
Stakeholder Mgmt
Excel
Fine-tuning
PyTorch
RAG
Deep Learning
Azure
A/B Testing
GCP
Kubernetes
Node.js
Spark
Go
SQL
Data Pipeline
AI roles with the most open positions
Normalized from active job posting titles
ML Engineer
AI Engineer
Research Scientist
MLOps Engineer
Computer Vision Eng
NLP Engineer
Skill mix in top AI postings
Proportion of top 20 skills by category — from active AI and ML job postings.
Reading the AI hiring landscape
What the demand data means for engineers targeting AI and ML roles
Python is the entry point
Python appears in more AI and ML postings than any other skill — including ML frameworks. Teams building on PyTorch, TensorFlow or any GenAI stack list Python as a prerequisite. It is not a differentiator; it is the baseline assumption for every role on this list.
GenAI has split the skills list
LLM, RAG, transformers, embeddings and vector databases have moved into the top rankings. Many roles now split into two tracks: classical ML (scikit-learn, XGBoost, feature engineering) and GenAI (fine-tuning, retrieval-augmented generation, prompt pipelines). Identifying which track a posting targets tells you which skills to lead with.
MLOps is no longer optional
Cloud platform skills — AWS SageMaker, Azure ML, Vertex AI, Kubernetes, Docker and MLflow — appear alongside model skills in the majority of mid-level and senior postings. Engineers are now expected to deploy, monitor and iterate models without handing off to a dedicated infrastructure team.
PyTorch has overtaken TensorFlow
PyTorch now leads TensorFlow in most new-hire postings, driven by its dominance in research and adoption by major model providers. JAX is rising in high-performance computing roles. Hugging Face Transformers bridges both — it is the library most teams use regardless of their underlying framework preference.
How this intelligence is gathered
Methodology behind the rankings, refreshed weekly
Job listings
AI and ML job postings are scraped daily from company career pages and aggregated job boards. Each listing is deduplicated and tagged with a normalised role category. Skills are extracted from each description and stored as weekly snapshots — so the rankings reflect what employers are actively hiring for right now, not six months ago.
Skill rankings
Rankings reflect how frequently each skill appears in active job listings — a direct measure of employer demand, not survey opinions or social media popularity. Percentages shown are share of all current AI listings. A skill's rank can shift week-over-week as postings open and close. The category breakdown shows how demand is currently split across languages, frameworks, GenAI and cloud infrastructure.
Explore related intelligence
Job data from active listings · Updated weekly