MLOps/LLMOps Engineer
NicheAlso known as: ML Platform Engineer, LLMOps Engineer, AI Infrastructure Engineer
Build and maintain the infrastructure pipelines that deploy, monitor, and scale machine learning and large language models in production.
Salary Range
The highest-paid specialization or seniority level for mlops/llmops engineers.
About 1 in 13 reaches this level
Field of ~30-50K practitioners (est., no BLS code — folded into SOC 15-1252 Software Developers / 15-2051 Data Scientists); only the top ~8% (~3,200) reach Principal MLOps Engineer or Director of ML Infrastructure at ~$300K total comp.
Salary data based on 2025 BLS, Glassdoor, and industry reports. Actual compensation varies by location, experience, and employer.
How to Become One
This career typically requires a bachelor's degree. Here are the top colleges for it:
Cost to Qualify
Four years of tuition and required fees runs about $56K at a typical public college in our list (in-state) and about $288K at a typical private one. Both are pricier than the US national averages (about $48K public in-state, $180K private nonprofit, College Board 2025-26) because our 161-college dataset only includes nationally-ranked schools, not every US college. This excludes room and board, which we show separately on each college's page.
Sticker price, not what most people pay — scholarships, aid and in-state status all move it. Room and board is shown separately on each college's page.
AI Risk Assessment
MLOps and LLMOps engineers build the systems that put machine-learning models and large language models to work: pipelines that train and release models, the servers that run them, and the monitoring that catches problems. There is no government category for this job. Its closest relative is software development, and the evidence there points two ways.
Demand is growing because of AI itself. The Bureau of Labor Statistics projects software developer jobs to grow 10% from 2025 to 2035, much faster than average, with about 106,100 openings a year, and names the spread of software for AI as one reason. Indeed job-listing data reported by CIO shows machine-learning skills asked for in about 3% of job listings in 2024 and over 5% in 2025.
The risk is in how people get in. Much of this job is writing code, scripts and configuration files, the kind of work AI tools handle best. A 2025 Microsoft Research study of AI chatbot use put software developers in the top sixth of 785 occupations for how much of their work AI can help with (Microsoft sells AI tools, and the authors warn a high score does not by itself mean job losses). A Stanford study of payroll data found that employment of software developers aged 22 to 25 had fallen nearly 20% by September 2025 from its late-2022 peak, while employment of experienced workers held steady.
That is a 3: strong demand, but the junior, code-heavy way in is exactly what AI is squeezing. It sits below software engineering (4) because the job grows as more companies put AI into use. This field moves fast, so treat the score as uncertain. What would change it: companies using managed AI platforms and AI agents to run model pipelines with much smaller teams would push it to 4. Junior MLOps hiring holding up as AI coding tools spread would bring it to 2.
Sources
Ratings reflect a 10-year outlook based on 2025-2026 research, weighted toward entry-level impact. Individual outcomes will vary.
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