AIML Engineer, Applied Data Science

Imagine what you could do here. At Apple new ideas have a way of becoming great products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could you passionate about taking AI from prototype to production at scalenDo you enjoy the craft of prompt engineering retrieval optimization and groundingnCan you build AI systems that are not just impressive demos but reliable production toolsnnThe Applied Data Science team within Legal Operations is building production-grade AI for a global legal organization. The AI/ML Engineer role is central to this mission prototyping AI solutions then scaling them to production systems that attorneys rely on every day.

The AI/ML Engineer builds AI capabilities from prototype to production. You will develop prompt engineering solutions RAG pipelines AI agents and evaluation frameworks starting with rapid prototypes to validate use cases then engineering them into scalable production-grade systems. This role requires both the creativity to explore whats possible and the rigor to build whats reliable.

Prototype AI solutions to rapidly validate use cases and demonstrate feasibilitynScale successful prototypes into production-grade systems with reliability monitoring and maintainabilitynImplement prompt engineering solutions optimized for legal use casesnBuild and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases and knowledge graphsnDevelop context engineering approaches that leverage the semantic layer for improved accuracynImplement grounding mechanisms to reduce hallucinations and improve factual accuracynBuild evaluation frameworks to measure AI accuracy relevance and safety across use casesnIntegrate AI capabilities with legal workflows (CLM matter management eBilling)nDevelop AI agent solutions for automation use cases across legal operationsnImplement guardrails and safety mechanisms for production AI systemsnCollaborate with AI Architect on system design and technical standardsnSupport AI Product Developers with APIs integration patterns and technical guidance

4 years of delivering solutions in AI/ML engineering NLP or related rolesnStrong proficiency in Python and ML frameworks (PyTorch TensorFlow or similar)nExperience with LLM APIs (OpenAI Anthropic or similar)nExperience with RAG architectures and vector databasesnUnderstanding of prompt engineering techniques and best practicesnExperience taking AI systems from prototype to productionnExperience with evaluation frameworks for AI systemsnSupporting AI applications in production

Experience with LangChain LlamaIndex or similar LLM orchestration frameworksnExperience with agentic AI frameworks (LangGraph CrewAI or similar)nFamiliarity with knowledge graphs and GraphRAG patternsnExperience with AI evaluation tools (RAGAS DeepEval or similar)nKnowledge of legal domain and legal NLP applicationsnExperience with guardrails and safety frameworks (Guardrails AI NeMo Guardrails)nUnderstanding of MCP (Model Context Protocol) or similar integration patternsnExperience deploying and monitoring AI systems at scalenTrack record of shipping AI products that users rely on