Mohamed A M Elansary, PhD
Target: Senior / Staff ML Research Scientist, Agents — Scale AI (ACE)
Sourced insights
- Scale RL Environments: Nearly half of Scale's new data-training projects involve RL environments; agents are scored with expert verifiers on real system-state changes — not whether they produced plausible text. ACE thesis in product form: environments, reward-worthy signals, data programs for tool use / computer use / coding agents. Source: scale.com/blog/rl-environments
- SWE Atlas: Across 284 coding-agent tasks (Codebase QnA, Test Writing, Refactoring), top systems cluster in the 40s (<50%); investigation correlates with success; "a coding agent's capability is inseparable from the environment it operates in." Hard agent evals + env quality — ACE JD nouns. Source: scale.com/blog/swe-atlas-complete
Proof — shipped agents + PhD UQ
- Production multi-tenant agentic LLM systems (Claude, GPT, Gemini): retrieval, query routing, tool-use, per-tenant data isolation — WhatsApp AI receptionist + voice booking agents in live use (Vertexium).
- Reliable Python/API automation for compliance, CRM data quality, and monitoring workflows — shipping over demos.
- PhD Environmental Engineering, TAMUK 2022: hydrologic uncertainty quantification — multi-basin ensemble forecasts on HPC (USGS/NOAA/NASA) as failure-mode / hard-eval rigor for agent evaluation.
- Honest frame: shipped agentic systems + UQ/eval — not OpenHands/LangGraph/fine-tune paper ownership.
- The PhD who ships. Prefer Seattle · prefer take-home when interview format allows.