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Forward Deployed Software Engineer

Pareto-ai

Remote · US$160k – $300kAI

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About this role

ABOUT PARETO

Humanity is in a virtuous cycle: human insight improves AI, and better AI expands what people can do. Sustaining it depends on the one input that can't be automated: expert human judgment https://pareto.ai/blog/debating-persuasive-llms-truthful-answers.

At Pareto, we build the platform that turns that judgment into the data https://pareto.ai/blog/community-driven-knowledge-resource-ai, evals https://pareto.ai/blog/introducing-attunebench, and RL environments frontier models https://pareto.ai/blog/llm-metacognition-shared-and-shallow learn from. We work with leading frontier labs like Anthropic and GDM, and we give skilled people everywhere a way to shape the future of AI and share in what it creates.

This RL environment and human-data infrastructure is already in production. Our job now is to scale it.

About This Role

Forward Deployed Engineers sit at the boundary between Pareto's engineering team and the researchers at the frontier labs we work with. You build directly on our platform to solve specific data and eval problems those teams can't solve themselves, and you own what you ship through to production.

This isn't a support role. You'll read research specs, write code, design evals, and build custom tooling that ends up inside model training pipelines. The feedback loop is tight. What you build shapes what the models learn.

What You'll Do

- Partner with AI researchers and TPMs at our client labs to understand their data and eval requirements, then build working solutions against them

- Build custom web applications, evaluation datasets, and internal tooling on top of the Pareto platform

- Write technical documentation and guides that client teams can actually use

- Spot gaps between what our platform does and what clients need, and feed those back into the product roadmap

- Present and demo solutions to technical audiences

What You'll Need

- Strong foundation in Python and/or TypeScript

- Experience with data pipelines, analytics, or eval frameworks. Comfortable reasoning about model inputs and outputs

- Clear written and verbal English communication. You're the interface between our engineering team and the client's researchers

- Based in the US (San Francisco), with ability to travel to client sites in California for key project milestones

You'll Stand Out If You Have

- Experience building on LLM APIs or running evals in a production context

- Familiarity with our stack: Django 5, React 18.2, AWS (Fargate/ECS/RDS)

- Prior client-facing or solutions engineering experience in an AI or ML context

- Background in CS, Math, Stats, or a related analytical field

You Probably Aren't the Fit If

- You need well-defined specs before you start building. Requirements here evolve with the research.

- You prefer working at arm's length from stakeholders. This role is high-contact. That's intentional.

- Context-switching bothers you. FDEs move between data engineering, eval design, and client work in the same week.

Compensation

$160K–$300K depending on level and experience. Equity at every level. We share level-specific ranges early in the process.

Why Pareto

You'd be working directly inside the data pipelines that train frontier models at Anthropic and GDM. Not adjacent to it. Not downstream. The work lands in production. Equity is part of the package at every level.

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