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OuterSignal

Research Engineer, Applied AI Engineering

Posted 3 Days Ago
Hybrid
New York City, NY
Mid level
Hybrid
New York City, NY
Mid level
Build and improve production AI/data pipelines, design model evaluation workflows and Jupyter analyses, add observability to AI systems, experiment with models/retrieval/prompt architectures, integrate and abstract AI APIs, and help define inference serving, fine-tuning, and dataset-generation infrastructure.
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About OuterSignal

We are building the customer intelligence layer for commerce. Brands know when an order comes in, but they only see ~5% of the real story. We show them the other 95%: not just who bought, but who that person is — the execs, influencers, journalists, retail buyers, investors, and everyday customers who become a brand’s best evangelists. Our platform enriches every order in real time with professional and personal signals, builds personas, and powers everything from surprise-and-delight outreach to smarter email flows, analytics, and BD leads. We’re a small, high-performing team building the category-defining platform for e-commerce customer intelligence, backed by a world-class investor base.

About This Role:

This is a backend-focused software engineering role specializing in applying ML/AI to user-facing products. You will work on the systems that power OuterSignal’s AI/data pipeline: prompt chaining, eval design, research APIs, model routing, and prod orchestration. The evolution of this role will include inference serving, fine-tuning, and synthetic dataset generation.

What You’ll Do:
  • Build and improve production AI/data pipelines that run across LLMs, APIs, databases, and workflow systems like Temporal, Postgres, ClickHouse, and Kubernetes.

  • Design evals and build Jupyter notebooks that help us measure model behavior, data quality, extraction accuracy, and end-to-end customer impact.

  • Build observability into AI workflows so we can understand cost, latency, reliability, and quality.

  • Experiment with new models, retrieval strategies, structured-output techniques, prompt/program architectures, and model-routing approaches.

  • Integrate with fast-changing research and AI APIs, understand their behavior deeply, and build robust abstractions around them.

  • Help define the foundation for future inference serving, fine-tuning, dataset generation, and model evaluation infrastructure.

Who You Are:
  • A strong engineer who can reason through distributed systems, data pipelines, databases, and are comfortable working across varying programming languages.

  • You are extremely AI-fluent and actively use modern AI tools to move faster.

  • You have strong first-principles thinking and can turn ambiguous problems into hypotheses, experiments, and shipped systems.

  • You have good judgment and taste: you simplify aggressively, avoid unnecessary complexity, and care about maintainability.

  • You care about measurement. You do not trust vibes when evals, tests, traces, or data can tell you what is actually happening.

  • Bonus: You have experience with PyTorch, Hugging Face, vLLM, Ray, MLflow, RAG, fine-tuning & RL, inference serving, and/or model evaluation systems.

Why Join Now:
  • Early seat: You’ll help shape the DNA of OuterSignal’s Applied AI Engineering org from the beginning.

  • Massive upside: Meaningful equity in a venture-backed company defining a new category in commerce intelligence.

  • Real AI systems: You’ll work on production AI that directly affects customers, data quality, and revenue — not demos or toy agents.

  • Big surface area: You’ll help connect research ideas to production systems and customer-facing product.

  • Right moment: We’re past prototype, real brands already rely on us, and we have strong PMF — but the ceiling is still wide open.

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