Associate, AI/ML Engineer

Legend Biotech is a global biotechnology company dedicated to treating life-threatening diseases. They are seeking an Associate AI/ML Engineer to join their Data & AI team, where the role involves designing, building, testing, and deploying production-grade Generative AI solutions and traditional machine learning models.

Responsibilities

• Build and iterate on LLM-powered features (e.g., chat, summarization, extraction, classification) using approved model providers and internal platforms
• Design retrieval-augmented generation (RAG) solutions, including document ingestion, chunking, embeddings, vector search, and prompt templates
• Develop and evaluate prompts, tools, and agentic workflows; implement guardrails (grounding, citations, refusal behavior) and improve reliability
• Create offline and online evaluation for GenAI systems (test sets, automated metrics, human review processes) and track quality over time
• Assist with developing, training, and evaluating traditional ML models when needed (e.g., classification, regression, anomaly detection, recommendation)
• Clean, preprocess, and analyze structured and unstructured data; build reproducible data pipelines for model inputs and evaluation
• Collaborate with data scientists, software engineers, security, and product teams to translate business requirements into safe, scalable solutions
• Support deployment, monitoring, and cost/performance optimization for GenAI services (latency, token usage, caching, drift, incident response)
• Write clean, maintainable, and well-documented code; contribute to code reviews, runbooks, and user documentation
• Works under guidance to make day-to-day technical decisions such as selecting baseline prompts/RAG patterns, defining evaluation criteria (quality, safety, latency, cost), and proposing experiment plans
• Escalates architecture, production rollout, security, and data governance decisions to senior engineers/tech lead; contributes input through code reviews, documentation, and demos

Skills

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field (or equivalent practical experience)
• Internship, academic project, or capstone experience building GenAI/LLM or ML applications
• Hands-on experience with at least one LLM framework/tooling (e.g., LangChain, LlamaIndex, Semantic Kernel) or equivalent custom orchestration
• Exposure to RAG building blocks (document ingestion, chunking, embeddings, vector databases/search)
• Familiarity with evaluation approaches for LLM systems (golden sets, qualitative rubrics, automated checks) and basic experiment tracking
• Familiarity with SQL and relational databases; experience working with unstructured text data is a plus
• Basic knowledge of cloud platforms (AWS, Azure, or GCP) and deploying services via APIs
• Experience with version control tools (Git/GitHub) and collaborative development workflows
• IT Skills: Python; Jupyter/VS Code; Git; Linux fundamentals; Docker basics; REST APIs; SQL; basic CI/CD concepts; familiarity with LLM APIs and orchestration frameworks (e.g., LangChain/LlamaIndex/Semantic Kernel); embeddings and vector databases/search (e.g., Pinecone/FAISS/Azure AI Search or equivalent); experiment tracking/evaluation tooling (e.g., MLflow or equivalent); basic monitoring/observability concepts (logs, traces, latency, token usage)

Benefits

• Medical, dental, and vision insurance
• 401(k) retirement plan with a company match that vests fully on day one
• Eight (8) weeks of paid parental leave after just three (3) months of employment
• Paid time off policy that includes vacation time, personal time, sick time, floating holidays, and eleven (11) company holidays
• Flexible spending and health savings accounts
• Life and AD&D insurance
• Short- and long-term disability coverage
• Legal assistance
• Supplemental plans such as pet, critical illness, accident, and hospital indemnity insurance
• Voluntary commuter benefits
• Family planning and care resources
• Well-being initiatives
• Peer-to-peer recognition programs

Company Overview

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