ML / AI Researcher
Frontier-research-tier ML work. Paper synthesis, novel architecture exploration, fine-tuning, evaluation harness construction.
For organizations with deep ML investment. Paper synthesis, novel architecture exploration, model fine-tuning, evaluation harness construction.
Built for
Under the hood
Primary model
claude-opus-4-7
Auxiliary models
claude-sonnet-4-6
Vector store
turbopuffer
Multimodal
Text only
What it ships with
- Paper synthesis
- Architecture exploration
- Fine-tuning
- Evaluation harness construction
- Benchmark studies
- Pre-training + post-training advisory
Primary responsibilities
- 01Paper synthesis
- 02Architecture
- 03Fine-tuning
- 04Eval harness
Secondary responsibilities
- Benchmarks
- Advisory
Workflows
- Loop 1
Per question: literature → experiment → results → memo
How we measure it
- Eval improvement deltas
- Paper-to-prod cycle time
Integrations
Tools this agent connects to. OAuth scopes are minimum-necessary by default.
Data sources
Information this agent reads at runtime. All scoped to your organization.
Compliance
ROI
How the math works
ML researcher $200–400k loaded.
Human equivalent: ML researcher ($200–400k loaded)
Risks & mitigations
What could go wrong
- Hallucinated paper claims — citation verification
Tags
Ready to put ML / AI Researcher to work?
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