Academic Content Developer - ML Platform and Inference Engineer
Contractual
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You'll build evaluation systems, backend services, and product features to measure and improve applied AI in production, working at the intersection of research and product. The role requires at least three years of experience as a software, infrastructure, or product engineer deploying production systems, strong Python skills, and hands-on cloud deployment experience. Key expertise includes building evaluation pipelines and benchmarks for ML systems, developing APIs and backend services, operating cloud infrastructure, and creating dashboards to visualize performance. Remote within the United States; $180,000 to $260,000 annually.
Written from this posting by Neural Jobs AI. The full description is below.
As an AI Infrastructure / Product Engineer, you will work at the intersection of AI research and product, helping turn experiments into dependable tools for legal work. You will build evaluation systems, backend services, and product features that help measure and improve applied AI in production.
Build repeatable benchmarks and evaluation pipelines for model accuracy, hallucinations, retrieval quality, latency, and cost.
Create dashboards that make system performance changes visible to the team.
Develop production retrieval, drafting, document, and agent workflows from research prototypes.
Build backend services, APIs, and internal tools to test and release improvements.
Deploy and operate cloud infrastructure, including monitoring, databases, and delivery pipelines.
Collaborate with AI research while staying connected to product and user needs.
At least 3 years of experience as a software, infrastructure, or product engineer building and deploying production systems.
Strong Python skills and hands-on experience deploying software to the cloud.
Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems.
Experience with APIs, databases, backend services, deployment pipelines, and systems that turn experimental code into maintainable products.
Experience building dashboards or monitoring systems to visualize performance, and operating cloud deployments reliably.
Full-stack experience is a plus. Familiarity with FastAPI, Docker, React, Next.js, Postgres, vector databases, LLMs, retrieval-augmented generation, agents, AI benchmarks, or document automation is helpful.
Annual base salary is $180,000 to $260,000 USD, depending on relevant skills, experience, and role scope. Visa sponsorship is not available.
Remote within the United States.
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