Job Description
Legend Biotech is a global biotechnology company dedicated to treating, and one day curing, life-threatening diseases. Headquartered in Somerset, New Jersey, we are developing advanced cell therapies across a diverse array of technology platforms, including autologous and allogenic chimeric antigen receptor T-cell, T-cell receptor (TCR-T), and natural killer (NK) cell-based immunotherapy. From our three RD sites around the world, we apply these innovative technologies to pursue the discovery of safe, efficacious and cutting-edge therapeutics for patients worldwide.
Legend Biotech entered into a global collaboration agreement with Janssen, one of the pharmaceutical companies of Johnson Johnson, to jointly develop and commercialize ciltacabtagene autolecuel (cilta-cel). Our strategic partnership is designed to combine the strengths and expertise of both companies to advance the promise of an immunotherapy in the treatment of multiple myeloma.
Legend Biotech is seeking a Senior AI/ML Engineer, Production AI (Contractor) as part of the IT team based in Somerset, NJ.
Role Overview
We are seeking a Senior AI/ML Engineer with strong experience delivering production-grade ML and Generative AI solutions. In this role you will do model development, design, deploy, monitor, and govern enterprise-ready ML and GenAI systems that are scalable, auditable, and compliant with internal AI policies and regulatory expectations.
You will help establish MLOps and GenAI Ops foundations, including evaluation, observability, and Responsible AI controls, enabling safe adoption of both predictive ML and GenAI use cases across the organization.
Key Responsibilities
AI/ML GenAI Engineering
Design, build, and deploy production-grade ML and Generative AI solutions, moving from prototypes to hardened services.
Implement GenAI patterns such as:
Retrieval-augmented generation (RAG).
Prompt engineering and prompt versioning.
Embedding pipelines and vector search.
Secure API-based model access.
Ensure AI systems meet enterprise standards for scalability, performance, reliability, and security.
MLOps GenAI Ops Frameworks
Build or configure end-to-end MLOps and GenAI Ops frameworks covering:
Model and prompt versioning
Reproducible pipelines and CI/CD for ML and GenAI workloads
Controlled deployment and rollback strategies
Integrate AI workflows with enterprise data platforms, orchestration tools, and cloud infrastructure
Model GenAI Evaluation
Define evaluation frameworks for both ML and GenAI, including:
Model accuracy, robustness, and drift
LLM response quality, grounding, hallucination risk, and safety checks
Bias, fairness, and explainability assessments
Establish acceptance criteria and validation artifacts suitable for regulated and audit-ready environments
Observability Monitoring
Implement observability frameworks for ML and GenAI systems to monitor:
Model and LLM performance degradation
Data and embedding drift
Prompt and response behavior over time
Latency, failure modes, and usage patterns
Enable full logging and traceability to support investigations, audits, and continuous improvement
Responsible Ethical AI
Embed Responsible AI principles across the AI lifecycle, including:
Human-in-the-loop controls for GenAI-assisted workflows
Transparency, explainability, and proper-use disclosures
Strong data privacy, access control, and lineage discipline
Ensure GenAI features are opt-in, governed, and aligned with Legend’s AI policies and regulatory expectations
Collaboration Leadership
Partner with Data Engineering, Architecture, Security, QA, and Business teams
Translate business problems into well-scoped, governed AI and GenAI solutions
Contribute to enterprise AI standards, reference architectures, and platform roadmaps
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field
5+ years of hands-on experience deploying ML systems in production
Strong experie ... (truncated, view full listing at source)