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Research Engineer

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Research Engineer in USA

  • San Francisco, CA

Responsibilities

  • Own evaluation infrastructure for quickly configuring, concurrently running, automatically executing, and monitoring modeling tests.
  • Implement deterministic, traceable measurement pipelines according to scientists’ specifications.
  • Maintain versioned evaluation datasets, including held-out sets excluded from training.
  • Build and maintain pipelines for human-participant data, external datasets, and model-training data, including participant record linkage.
  • Keep research code aligned with the production product so validated improvements can ship promptly.
  • Detect and prevent threats to evaluation validity.
  • Track compute and API spending across experiments and assess production-stage cost implications.
  • Manage repositories, code review, documentation, and reproducible coding workflows.
  • Identify opportunities to improve implementation correctness and efficiency and propose changes.

Requirements

  • Several years of software engineering experience, including experience supporting researchers in a lab or comparable setting.
  • Experience translating scientific requirements and experiment designs into code.
  • Experience building and operating large-scale data pipelines on human-behavior data and validating them against researcher-defined criteria.
  • Strong Python skills, including the ability to read and audit code produced by agentic coding tools.
  • Knowledge of file systems, software libraries, databases, SQL, tabular data, and Git-based workflows.
  • Experience with cloud infrastructure and concurrent job execution.
  • Working knowledge of machine learning, transformer-based language models, model APIs, and fine-tuning.
  • Demonstrated ability to write deterministic, reproducible, cost-aware, and well-documented code.
  • Preferred: experience engineering LLM systems, including prompt pipelines, evaluation harnesses, embedding computation, agentic systems, or fine-tuning infrastructure.
  • Preferred: experience fine-tuning open-weight language models on multi-GPU hardware.
  • Preferred: experience serving open-weight models with vLLM or SGLang, including batched inference and prefix caching.
  • Preferred: experience with experiment tracking, machine-learning cost monitoring, GPU provisioning across cloud providers, survey or panel data, data collection platforms, model activations, generative agents, digital twins, or human-respondent simulation.

Salary: $200k - $240k/yr

Outset

Outset builds an AI‑moderated research platform that runs qualitative user interviews and automates analysis for product, UX, and marketing teams. Delivered as a SaaS platform, it helps organizations conduct discovery, concept, brand, and pricing research at scale. Founded in 2022 and headquarter...

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