Senior AI/ML Engineer, Production AI (Contractor)

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 Legends 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

• Bachelors or Masters degree in Computer Science, Engineering, Data Science, or related field
• 5+ years of hands-on experience deploying ML systems in production
• Strong experience with:
  
  • Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
  • LLMs and GenAI tooling (commercial or open-source)
  • MLOps practices, pipelines, and automation
  • Cloud platforms (Azure, AWS, or GCP)
• Familiarity with vector databases, embedding strategies, and RAG & graph architectures
• Proven ability to design governed, observable, and secure AI systems
• Experience in biotech, life sciences, healthcare, or other GxP-relevant domains
• Extensive experience operating within enterprise SDLC and production IT processes.
• Demonstrated experience delivering AI systems through full system development lifecycle (SDLC).
• Experience implementing GenAI in enterprise or regulated environments.
• Exposure to AI governance, risk assessments, or validation frameworks.

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