Machine Learning Engineer Salary Guide 2025-2026: What the Data Shows
ML engineer compensation is the highest in technology right now — and the spread between levels is wider than most engineers realize. Here is what the actual numbers look like, broken down by role, seniority, location, and specialization.
Overall ML Engineer Salary Ranges in 2025
Analysis of over 5,000 ML engineer job postings from January through June 2025 shows the following compensation bands: average minimum compensation of $137,444, average midpoint of $175,709, and average maximum of $213,973. For full-time positions specifically, the average midpoint sits at $174,642.
These numbers represent a modest increase over 2024 — minimum compensation is up 2.3% and maximum is up 1.9% year-over-year. The market has stabilized after the compensation spike of 2021-2022, settling into a sustainable range that reflects genuine demand rather than speculative hiring.
Salary by Specialization
Not all ML roles pay equally. Here is how specialization affects compensation at the midpoint level in 2025: Machine Learning Engineer (general): $168,000-$185,000. LLM Engineer: $175,000-$210,000. GenAI Engineer: $172,000-$205,000. MLOps Engineer: $160,000-$190,000. NLP Engineer: $165,000-$195,000. Computer Vision Engineer: $162,000-$192,000. Applied Scientist: $180,000-$220,000. AI Research Scientist: $195,000-$260,000+.
LLM and GenAI specializations command a 10-15% premium over general ML engineering, reflecting the current intensity of demand for engineers who can work with large language models in production environments. Applied Scientists and Research Scientists sit at the top of the range, but these roles typically require graduate degrees and significant prior research experience.
Salary by Geography
The top five metros for ML engineering jobs — Silicon Valley, Seattle, New York, San Francisco, and Boston — also carry the highest compensation. Silicon Valley and San Francisco roles average 25-35% above national median. Seattle and New York average 15-20% above national median. Boston averages 10-15% above.
Dallas-Fort Worth is emerging as a meaningful secondary market, with ML engineering compensation typically running 10-15% below the national median but with significantly lower cost of living. Companies in the DFW tech corridor, including those partnered with firms like STAR Workforce Solutions, are increasingly competitive on total compensation including equity and benefits.
Remote ML Engineering Compensation
Remote ML engineering roles have largely converged to national median compensation rather than location-adjusted pay. A senior ML engineer working remotely for a San Francisco company typically earns national median rather than the SF premium. This represents a normalization from the 2021-2022 period when many remote roles paid Bay Area rates regardless of worker location.
The practical implication: remote roles are an excellent option for engineers in lower cost-of-living markets, representing a 20-30% effective income premium when adjusted for local purchasing power.
Skills That Move the Number
Within any given role and seniority level, certain skills consistently correlate with compensation at the top of the range rather than the middle: production LLM experience (fine-tuning, RLHF, inference optimization), distributed training at scale (multi-GPU, multi-node), vector database design and optimization, agentic AI system architecture, and model monitoring and drift detection in production. Each of these skills can shift compensation $15,000-$30,000 compared to candidates without them.
Finding ML Engineering Roles
All ML and AI engineering salaries on Rebuix are displayed on job listings where employers have provided compensation data. Every role is verified for genuine AI content — so the salaries you see are for actual ML engineering work, not software roles with “AI” added to the title.