Applied AI Scientist (PhD)

Outmarket Inc

$130K — $160K *
US-AnywhereRemote in United States
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in Computer Science, Machine Learning, NLP, or related field.
  • Strong research background with publications in top-tier AI venues such as NeurIPS, ACL, ICML, or EMNLP.
  • Hands-on experience with LLMs, transformers, embeddings, or neural information retrieval.
  • Proficiency in Python and ML tooling like PyTorch, Hugging Face, and LangChain.
  • Track record of applying research to practical, production-oriented systems.

Responsibilities

  • Research and develop LLM-based solutions for NLP and document intelligence.
  • Design and enhance prompt strategies and retrieval-augmented generation systems.
  • Collaborate with product and engineering teams to integrate AI into customer workflows.
  • Build evaluation pipelines for accuracy, performance, and robustness.
  • Stay current with new research and rapidly test techniques in practical settings.
  • Operate as both a scientist and builder with direct responsibility for ideas' survival with real data.

Benefits

  • High-impact role on a fast-moving team that builds with purpose.
  • Competitive compensation and meaningful equity.
  • Remote-first flexibility.
  • Access to real data, real users, and fast feedback cycles.
  • Opportunity to bring advanced research to life in a major industry.
Full Job Description
ABOUT THE ROLE

We are hiring an Applied AI Scientist to push the frontier of what is possible with LLMs, NLP, and machine learning in real-world environments. This is not a role for someone who wants to optimize benchmarks in isolation and hand work off to someone else. It is a role for someone who wants to see advanced research become customer-facing product quickly.

You will work closely with founders, product leaders, and engineers to turn advanced AI techniques into systems that operate under real production constraints.
WHY THIS ROLE
  • Apply cutting-edge AI research to live customer workflows and production systems.
  • Work directly with founders and a highly experienced technical team.
  • Build solutions for document intelligence, quote comparison, workflow optimization, and other high-value use cases.
  • See your work move from research to deployment in weeks, not quarters.
  • Help define how applied AI creates advantage in a large, underserved market.
WHAT YOU'LL DO
  • Research and develop LLM-based solutions for NLP, document intelligence, semantic search, and data extraction.
  • Design and improve prompt strategies, retrieval-augmented generation systems, and fine-tuned models.
  • Partner with product and engineering teams to bring AI capabilities into customer-facing workflows.
  • Build evaluation pipelines and benchmarks for accuracy, performance, and robustness.
  • Stay current on new research and rapidly test promising techniques in practical settings.
  • Operate as both a scientist and builder, with direct responsibility for whether ideas survive contact with real data.
WHAT WE'RE LOOKING FOR
  • PhD in Computer Science, Machine Learning, NLP, or a related field.
  • Strong research background with publications in top-tier AI venues such as NeurIPS, ACL, ICML, or EMNLP.
  • Hands-on experience with LLMs, transformers, embeddings, or neural information retrieval.
  • Proficiency in Python and ML tooling such as PyTorch, Hugging Face, and LangChain.
  • Track record of applying research in practical, production-oriented systems.
  • Strong technical judgment about what is novel, what is useful, and what is actually ready to ship.
BONUS IF YOU HAVE
  • Experience with unstructured data such as PDFs, forms, contracts, or portals.
  • Background in enterprise or B2B AI applications.
  • Familiarity with insurance, legal, or document-heavy industries.
WHAT YOU'LL GET
  • A high-impact role on a team that moves quickly and builds with purpose.
  • Competitive compensation and meaningful equity.
  • Remote-first flexibility.
  • Access to real data, real users, and fast feedback cycles.
  • The opportunity to bring advanced research to life in a major industry.

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