Fine-tuning and Kubernetes frequently appear together in AI job postings, with 40 current openings requiring both skills. The most common role for this combination is AI/ML Engineer. Jobs requiring both skills pay up to $197K on average. Below you'll find detailed salary data, hiring companies, and related skill combinations.
Deploying LLM applications in production requires both Fine-tuning expertise and Kubernetes infrastructure skills. Kubernetes provides the compute, scaling, and serving layer, while Fine-tuning handles the AI application logic. The 40 roles listing both reflect the growing need for engineers who can bridge AI development and cloud operations.
Top Roles Requiring Fine-tuning + Kubernetes
AI/ML Engineer27 jobs
Prompt Engineer4 jobs
Data Engineer3 jobs
AI Software Engineer3 jobs
LLM Engineer2 jobs
AI Architect1 jobs
Career Impact
Professionals who combine Fine-tuning and Kubernetes earn a median salary ceiling of
$197K, compared to $228K for Fine-tuning alone and
$230K for Kubernetes alone. This 14% discount
reflects roles requiring both skills tend to be more common mid-level positions, while single-skill roles may skew toward senior or specialized positions with higher pay ceilings.
Based on our analysis of current AI job postings, 40 positions require both Fine-tuning and Kubernetes skills. The most common role for this combination is AI/ML Engineer.
Jobs requiring both Fine-tuning and Kubernetes pay an average of $135K to $197K based on 24 postings with disclosed compensation.
Jobs requiring both Fine-tuning and Kubernetes pay $197K on average (max), compared to $228K for Fine-tuning alone and $230K for Kubernetes alone. That represents a 14% discount for having both skills.
The most common roles requiring both Fine-tuning and Kubernetes are: AI/ML Engineer, Prompt Engineer, Data Engineer, AI Software 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 40 job postings that list both Fine-tuning and Kubernetes
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.
