Model Training & Post-Training (MTS)
Engineers in this role build the systems and data pipelines that turn real-world model usage into measurable improvements, working across evaluation, synthetic data generation, reinforcement learning, and post-training infrastructure. They identify high-value failure modes in deployed models, design targeted interventions through data curation and reward signals, and validate improvements before integration into production training runs. This hands-on work bridges research and deployment, requiring both strong ML fundamentals and pragmatic engineering to close the gap between benchmark performance and useful, reliable behavior in production systems.
Measured across 75 of 76 open postings.
This role is advertised at 2 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 | 24%(18) | — | $440k |
| Staff / Principal | 60%(45) | — | $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 Most companies do not publish a salary band, so pay is indicative rather than a market rate. 3 levels with fewer than 10 open postings are not shown.
“Demonstrate strong technical fluency and uses AI tools to accelerate policy development, evaluate model behavior, analyze failure patterns”
“work on problems at the frontier of agentic AI, where challenges in alignment, reliability, and scalability are deeply intertwined”
“turn model usage into rigorous evaluations, targeted training data, and measurable improvements in future generations of models”
“You have improved LLM-powered, agent-powered, or AI-product systems through evals, feedback loops, data curation, prompting, model adaptation, or model selection.”
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.
Skills
What companies are looking for in this role.
Post-training and alignment methods
Large-scale model training
Research experiment design
ML systems development
Model architecture design
Training data curation
Data pipeline engineering
Distributed systems architecture
Model behavior analysis
Research-to-production translation
Data quality and governance
Annotation schema design
AI evaluation design
Agentic system research
Frontier AI research
Synthetic data generation
Inference performance optimization
Agent workflow design
Computer vision and perception
Agent system architecture and development
Research rigor and reproducibility
Technology
The tools and technologies that define this role.
Open Jobs
76 open Model Training & Post-Training (MTS) jobs across 27 companies.
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