Machine Learning Engineer
Engineers in this role develop and operate production machine learning systems that power real-world AI products, from recommendation and ranking systems at fintech companies to perception models for autonomous vehicles and multimodal foundation models. They bridge research and production by building scalable training infrastructure, data pipelines, and deployment systems that handle massive datasets and complex model architectures while maintaining reliability and performance at scale. These roles typically sit within specialized teams—whether perception, infrastructure, or applied ML—that collaborate closely with product, research, and systems engineers to translate model innovations into deployed systems serving millions of users or real-world safety-critical applications.
Measured across 221 of 232 open postings.
This role is advertised at 3 levels, so a single figure for the role would describe none of them. Experience and pay are the midpoints for each level on its own.
| Level | Share | Median years | Median pay |
|---|---|---|---|
| Mid | 40%(88) | 3 | $313k |
| Senior | 24%(52) | 5 | — |
| Staff / Principal | 29%(65) | 6 | $303k |
A dash means too few postings stated it to report a midpoint. Most companies do not publish a salary band, so pay is indicative rather than a market rate. 2 levels with fewer than 10 open postings are not shown.
“We're big users of agentic development and operations. You'll have access to best-in-class models, agents, GPUs, storage and cloud services”
“Train and fine-tune large language models (LLMs) for clinical reasoning, medical question answering, evidence-grounded generation”
“Your job is to make that process faster, cheaper, and more rigorous with ML and AI”
“build production systems that learn from privacy-protected product and experimentation data to generate evidence-backed insights”
Requirements are a share of every open posting, so a role missing from this list is one where almost nobody asks. Work mode is different: many postings never say, so that figure counts only the ones that do. A posting stops being advertised when it is filled, cancelled or reorganised, so read the last figure as how long these stay on the market, not as time to hire.
Skills
What companies are looking for in this role.
ML systems development
Large-scale model training
Distributed systems architecture
Data pipeline engineering
Research-to-production translation
Systems performance optimization
Model architecture design
Post-training and alignment methods
Backend and API engineering
Training data curation
Research experiment design
AI evaluation design
Inference performance optimization
Computer vision and perception
ML platform engineering
LLM application development
Retrieval and ranking systems
Agentic system research
Agent system architecture and development
Technology
The tools and technologies that define this role.
Open Jobs
232 open Machine Learning Engineer jobs across 64 companies.
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