Senior AI/Machine Learning Engineer (exp with pharma and gxp app/environment highly preferred)

Job details

Senior AI Machine Learning Enginee

rBridgewater, NJ (3 days/week

)6 months + RT

H
Job Title Senior AI/ML Engineer – Production AI Locati

on
Role Overv

iewWe 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 organizati

on.
Key Responsibili

ties• AI/ML & GenAI Enginee

ringo Design, build, and deploy production-grade ML and Generative AI solutions, moving from prototypes to hardened services o Implement GenAI patterns such as: ▪ Retrieval-augmented generation (

RAG)▪ Prompt engineering and prompt versio

ning▪ Embedding pipelines and vector se

arch▪ Secure API-based model ac

cesso Ensure AI systems meet enterprise standards for scalability, performance, reliability, and secu

rity• MLOps & GenAI Ops Framew

orkso Build or configure end-to

-endMLOps and GenAI Ops frameworks cover

ing:▪ Model and prompt versio

ning▪ Reproducible pipelines and CI/CD for ML and GenAI workl

oads▪ Controlled deployment and rollback strate

gieso Integrate AI workflows with enterprise data platforms, orchestration tools, and cloud infrastruc

ture• Model & GenAI Evalua

tiono Define evaluation frameworks for both ML and GenAI, includ

ing:▪ Model accuracy, robustness, and d

rift▪ LLM response quality, grounding, hallucination risk, and safety ch

ecks▪ Bias, fairness, and explainability assessm

entso Establish acceptance criteria and validation artifacts suitable for regulated and audit-ready environm

ents• Observability & Monito

ringo Implement observability frameworks for ML and GenAI systems to moni

tor:▪ Model and LLM performance degrada

tion▪ Data and embedding d

rift▪ Prompt and response behavior over

time▪ Latency, failure modes, and usage patt

ernso Enable full logging and traceability to support investigations, audits, and continuous improve

ment• Responsible & Ethica

l AIo Embed Responsible AI principles across the AI lifecycle, includ

ing:▪ Human-in-the-loop controls for GenAI-assisted workf

lows▪ Transparency, explainability, and proper-use disclos

ures▪ Strong data privacy, access control, and lineage discip

lineo Ensure GenAI features are opt-in, governed, and aligned with Legend’s AI policies and regulatory expectations Collaboration & Leader

ship• Partner with Data Engineering, Architecture, Security, QA, and Business t

eams• Translate business problems into well-scoped, governed AI and GenAI solut

ions• Contribute to enterprise AI standards, reference architectures, and platform roadmaps Requ

ired
Qualifica

tions• 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 produ

ction• Strong experience

with:o Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-l

earn)o LLMs and GenAI tooling (commercial or open-so

urce)o MLOps practices, pipelines, and automation o Cloud platforms (Azure, AWS, or

GCP)• Familiarity with vector databases, embedding strategies, and RAG & graph architec

tures• Proven ability to design governed, observable, and secure AI sy

stems• Experience in biotech, life sciences, healthcare, or other GxP-relevant do

mains• Extensive experience operating within enterprise SDLC and production IT proce

sses.• Demonstrated experience delivering AI systems through full system development lifecycle (S

DLC).
Nice t

o Have• Experience implementing GenAI in enterprise or regulated enviro

nments• Exposure to AI governance, risk assessments, or validation fram