Latest ML Engineering jobs at Harvey

Leads the design and operation of reliable, scalable model infrastructure powering AI inference across multiple providers. Requires 7+ years of distributed-systems engineering experience, strong programming skills, and expertise in production reliability and cloud infrastructure.

Lead design and development of Harvey's Model Infrastructure platform powering all AI requests, including unified model controller, intelligent routing, multi-provider integrations, observability, and capacity management for high reliability, low latency, and efficiency. Requires 7+ years building large-scale distributed systems with strong programming and leadership skills; AI/LLM infrastructure experience preferred.

Build and optimize AI agents for legal workflows at Harvey. Design environments, actions, evaluations, tools, and infrastructure for high-performance domain-specific agents using LLMs.

Build core AI platform infrastructure at Harvey including model routing, context management, agent architecture, and shared evaluation frameworks that power all agentic legal AI products. Requires 5+ years backend experience with 1+ year in AI/ML, production multi-model systems, and platform-building track record.

Research engineer focused on post-training LLMs and agents for legal work. Requires hands-on experience training open-weight models and strong Python/research engineering skills.

Builds AI agent systems for legal workflows, optimizing performance via prompt engineering, model selection, tools, and evaluations. Partners with customers/PMs to ship low-latency agents using Python and LLM APIs; requires 8+ years experience.

Build core AI platform infrastructure at Harvey including model routing, context engineering, agent infrastructure, and shared evaluation frameworks that power all agentic legal AI products. Requires 8+ years backend experience with 1+ year AI/ML focus and track record of technical leadership.

Build core AI platform infrastructure at Harvey including model routing, context management, evaluation frameworks, and shared abstractions for agentic AI products. Requires 5+ years backend experience with 1+ year in AI/ML, production multi-model systems, and strong platform-building skills.

Build AI agent systems for legal workflows, optimizing performance via prompt engineering, model selection, tools, and evals. Requires 3+ years experience, Python proficiency, and LLM/agent framework expertise for mid/senior/staff levels.