Strategic Projects Lead

Job not on LinkedIn

🕒 May 14

🇺🇸 United States – Remote

💵 $140k - $180k / year

⏰ Full Time

🟠 Senior

🧐 Strategy

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Pareto.AI

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

🤖 Artificial Intelligence

🤝 B2B

Artificial Intelligence • B2B

Pareto. AI is a human-centered partner for frontier AI research and development that orchestrates networks of domain specialists to produce context-rich, high-quality data, run experiments, and evaluate models. The company provides managed, on-demand expert teams (from PhDs and medical doctors to technical specialists) to help AI organizations scale expert-only capabilities, accelerate research, and deliver robust, high-fidelity datasets and evaluations.

📋 Description

• Design end-to-end data collection and evaluation pipelines for RLVR, RLHF, SFT, red-teaming, and model evaluation workflows. • Build, test, and iterate on AI agents that automate pipeline tasks — quality gate review, expert matching, output flagging, throughput anomaly detection. • Define data quality standards across annotation, evaluation, and expert output review. • Engage directly with AI researchers, TPMs, and PMs at client organizations. • Stay current with developments in LLM post-training, evaluation methodology, and data tooling.

🎯 Requirements

• Proficiency in Python and SQL for data manipulation, pipeline monitoring, and quality analysis • Working knowledge of LLM internals: RLHF/SFT training loops, how prompt structure affects output distribution, RL environment setup qualities (tool use) for agentic data collection / eval projects. • Hands-on experience with at least one agentic or LLM workflow framework (LangChain, DSPy, AutoGen, direct tool-use via API, or equivalent) • Demonstrated ownership of a data or ML pipeline from scoping through delivery — including quality design, not just throughput tracking • Strong written communication: you'll write technical guidelines and rubrics that distributed expert workers follow accurately, and you'll brief senior researchers on pipeline performance • Comfort operating with ambiguity in a fast-moving environment where model requirements shift and client priorities evolve

🏖️ Benefits

• Offers Equity