Manager, AI Engineering

4w4 weeks ago

Acadia Pharmaceuticals Inc.

San Diego, US · Full-time · $122,000 – $152,600

About this role

Acadia is committed to turning scientific promise into meaningful innovation for underserved neurological and rare disease communities. As Manager, AI Engineering, you will design, build, and deploy scalable AI/ML and GenAI solutions that deliver measurable business impact across R&D, Commercial, and Corporate functions.

In this role, you will contribute to the enterprise AI strategy and roadmap, providing technical input on use-case feasibility, architecture decisions, and build-vs-buy assessments. You will build and maintain scalable ML and LLM pipelines from data ingestion through production, adhering to ML Ops and LLM Ops standards for versioning, evaluation, observability, and rollback.

You will partner with business, analytics, IT, and security teams to identify and deliver high-value AI use cases across the organization. Additionally, you will evaluate and integrate AI platform components such as model endpoints, vector databases, agent frameworks, and guardrails in alignment with enterprise architecture standards.

You will contribute to responsible AI governance by supporting model documentation, risk assessment, bias testing, explainability, and compliance with regulations like NIST AI RMF and EU AI Act readiness. This role offers an opportunity to shape enterprise AI capabilities in a mission-driven pharmaceutical company.

Requirements

Master’s degree or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative discipline, or equivalent practical experience
Experience designing and deploying machine learning and statistical models in production environments
Hands-on experience with GenAI solutions and large language model pipelines
Proficiency in ML Ops and LLM Ops practices, including versioning, evaluation, observability, and rollback
Familiarity with AI governance frameworks such as NIST AI RMF and EU AI Act readiness
Ability to evaluate and integrate AI platform components including model endpoints, vector databases, and agent frameworks
Experience collaborating with cross-functional teams (business, IT, security) to deliver AI use cases

Responsibilities

Design, develop, validate, and deploy machine learning, statistical, and GenAI solutions that address complex business problems and support enterprise priorities
Contribute to execution of the enterprise AI strategy and roadmap by providing technical input on use-case feasibility, value hypotheses, architecture decisions, and build-vs-buy assessments
Build and maintain scalable ML and LLM pipelines from data ingestion through production, adhering to ML Ops and LLM Ops standards including versioning, evaluation, observability, and rollback
Partner with business, analytics, IT, and security teams to identify, prototype, and deliver high-value AI use cases across the organization
Evaluate and integrate AI and GenAI platform components such as model endpoints, vector databases, agent frameworks, and guardrails in alignment with enterprise architecture standards
Contribute to AI governance by supporting model documentation, lineage, risk assessment, bias testing, explainability, and compliance with applicable regulations and frameworks
Provide technical input into AI platform and vendor evaluations, including RFI/RFP activities and assessments of cost, security, and data residency
Support AI enablement efforts through development of reusable patterns, reference implementations, and technical documentation to accelerate adoption

Benefits

Hybrid work model requiring three days per week in office (San Diego, San Francisco, or Princeton)
Opportunity to contribute to enterprise AI strategy at a mission-driven pharmaceutical company
Work on cutting-edge AI/ML solutions in the neurological and rare disease therapeutic areas