What is Model Interpretability and how common is it in AI job postings?

Model Interpretability is a skill in the "ML Techniques" category. It currently appears in 168 active AI roles across 61 companies in our index.

Which companies are hiring for Model Interpretability?

The top employers with active AI roles mentioning Model Interpretability are: Amazon (21), Google (15), OpenAI (11), JPMorgan Chase (8), Salesforce (7).

Is demand for Model Interpretability growing?

Over the last 11 weeks, 120 new AI postings mentioned Model Interpretability. Demand is rising — up 130% in the last four weeks compared to the earliest four weeks in the window.

At which stage of AI development is Model Interpretability used?

Roles requiring Model Interpretability are concentrated in: agents (60%), post-training (14%), application (10%). These stages follow a seven-stage AI lifecycle from data preparation through to shipped product.

What skills are commonly paired with Model Interpretability?

Job postings that mention Model Interpretability most often also require: Machine Learning, Large Language Models (LLMs), Python, Agentic Systems, Production ML Systems.

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Model Interpretability

168 active AI roles across 61 companies mention Model Interpretability. Category: ML Techniques.

Demand trend

New AI postings mentioning Model Interpretability per week — 120 total over 11 weeks.

Function

All Engineering · 124 Research · 38 Product · 6

Status

All Active only

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AI score Recently posted Company A–Z

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11 AI roles requiring this skill.

Company	Title	Sector	AI score	Stage
Capital One	Applied Researcher II	Banking	9	L2
JPMorgan Chase	AI/ML Lead- Agentic AI	Banking	8	L4
JPMorgan Chase	Software Engineer III - AI/ML, Prompt Engineer	Banking	8	L4
JPMorgan Chase	Senior Quant Analytics Associate - Fraud Risk	Banking	8	L4
Capital One	Applied Researcher II (AI Foundations)	Banking	8	L1
JPMorgan Chase	Applied AI/ML - Vice President	Banking	8	L4
JPMorgan Chase	Director of Software Engineering	Banking	7	L4
Bank of America	Senior Engineer - Enterprise GenAI Platform Architect	Banking	7	L4
JPMorgan Chase	Applied AI ML Lead	Banking	7	L2
JPMorgan Chase	Product Manager, AI Platform	Banking	7	L4
JPMorgan Chase	Quantitative Trading & Research – Global Clearing – Vice President	Banking	7	L6

Frequently asked questions

What is Model Interpretability and how common is it in AI job postings?
Model Interpretability is a skill in the "ML Techniques" category. It currently appears in 168 active AI roles across 61 companies in our index.
Which companies are hiring for Model Interpretability?
The top employers with active AI roles mentioning Model Interpretability are: Amazon (21), Google (15), OpenAI (11), JPMorgan Chase (8), Salesforce (7).
Is demand for Model Interpretability growing?
Over the last 11 weeks, 120 new AI postings mentioned Model Interpretability. Demand is rising — up 130% in the last four weeks compared to the earliest four weeks in the window.
At which stage of AI development is Model Interpretability used?
Roles requiring Model Interpretability are concentrated in: agents (60%), post-training (14%), application (10%). These stages follow a seven-stage AI lifecycle from data preparation through to shipped product.
What skills are commonly paired with Model Interpretability?
Job postings that mention Model Interpretability most often also require: Machine Learning, Large Language Models (LLMs), Python, Agentic Systems, Production ML Systems.

Model Interpretability

Top employers

Often paired with

Demand trend

Frequently asked questions

Demand trend

Model Interpretability

Top employers

Often paired with

Frequently asked questions