Acadia is committed to turning scientific promise into meaningful innovation that makes the difference for underserved neurological and rare disease communities around the world. Our commercial portfolio includes the first and only FDA-approved treatments for Parkinsons disease psychosis and Rett syndrome. We are developing the next wave of therapeutic advancements with a robust and diverse pipeline that includes mid- to late-stage programs in Alzheimers disease psychosis and Lewy body dementia psychosis along with earlier-stage programs that address other underserved patient needs. At Acadia were here to be their difference.
Please note that this position can be based in San Diego CA San Francisco CA or Princeton NJ. Acadias hybrid model requires this role to work in our office three days per week on average.
Position Summary
The Manager AI Engineering plays a key role in advancing Acadias enterprise AI and analytics capabilities. This role designs builds and deploys scalable AI/ML and GenAI solutions that deliver measurable business impact across R&D Commercial and Corporate functions. As a core member of the Artificial Intelligence organization the Manager will contribute to the enterprise AI strategy support responsible AI governance and help operationalize advanced analytics and machine learning at scale across Acadia globally.
Primary 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 usecase feasibility value hypotheses architecture decisions and buildvsbuy assessments
Build and maintain scalable ML and LLM pipelines from data ingestion through production adhering to established 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 highvalue 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
Apply and uphold policies for AI lifecycle management bias/robustness testing explainability human oversight and incident response. Support mapping of AI controls to major frameworks and regulations (e.g. NIST AI RMF EU AI Act readiness) to ensure responsible and compliant AI deployment.
Ensure all data science work complies with global AI regulations ethical standards and applicable GxP processes.
Participate in cross-functional AI Governance Council activities as requested providing technical expertise on model risk and data science practices.
Other duties as assigned
Education/Experience/Skills
Masters degree or PhD in Data Science Statistics Computer Science Mathematics or a related quantitative discipline or equivalent practical experience
5 years of handson experience in applied data science and machine learning including model development deployment and production support
Advanced proficiency in Python and common ML frameworks and tools such as scikitlearn TensorFlow PyTorch and SQL
Practical experience with ML Ops and LLM Ops practices including model registries version control evaluation benchmarks and monitoring
Experience working with large language models GenAI technologies vector databases or agent frameworks
Experience operating in a regulated environment and following GxP or similar compliance processes
Willingness and ability to travel domestically and internationally
Physical Requirements
This role involves regular standing walking sitting and the use of hands for handling or operating equipment. The employee may also need to reach climb balance stoop kneel crouch and maintain visual verbal and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds. This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.
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Manager
About Acadia PharmaceuticalsAcadia is committed to turning scientific promise into meaningful innovation that makes the difference for underserved neurological and rare disease communities around the world. Our commercial portfolio includes the first and only FDA-approved treatments for Parkinsons d...
About Acadia Pharmaceuticals
Acadia is committed to turning scientific promise into meaningful innovation that makes the difference for underserved neurological and rare disease communities around the world. Our commercial portfolio includes the first and only FDA-approved treatments for Parkinsons disease psychosis and Rett syndrome. We are developing the next wave of therapeutic advancements with a robust and diverse pipeline that includes mid- to late-stage programs in Alzheimers disease psychosis and Lewy body dementia psychosis along with earlier-stage programs that address other underserved patient needs. At Acadia were here to be their difference.
Please note that this position can be based in San Diego CA San Francisco CA or Princeton NJ. Acadias hybrid model requires this role to work in our office three days per week on average.
Position Summary
The Manager AI Engineering plays a key role in advancing Acadias enterprise AI and analytics capabilities. This role designs builds and deploys scalable AI/ML and GenAI solutions that deliver measurable business impact across R&D Commercial and Corporate functions. As a core member of the Artificial Intelligence organization the Manager will contribute to the enterprise AI strategy support responsible AI governance and help operationalize advanced analytics and machine learning at scale across Acadia globally.
Primary 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 usecase feasibility value hypotheses architecture decisions and buildvsbuy assessments
Build and maintain scalable ML and LLM pipelines from data ingestion through production adhering to established 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 highvalue 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
Apply and uphold policies for AI lifecycle management bias/robustness testing explainability human oversight and incident response. Support mapping of AI controls to major frameworks and regulations (e.g. NIST AI RMF EU AI Act readiness) to ensure responsible and compliant AI deployment.
Ensure all data science work complies with global AI regulations ethical standards and applicable GxP processes.
Participate in cross-functional AI Governance Council activities as requested providing technical expertise on model risk and data science practices.
Other duties as assigned
Education/Experience/Skills
Masters degree or PhD in Data Science Statistics Computer Science Mathematics or a related quantitative discipline or equivalent practical experience
5 years of handson experience in applied data science and machine learning including model development deployment and production support
Advanced proficiency in Python and common ML frameworks and tools such as scikitlearn TensorFlow PyTorch and SQL
Practical experience with ML Ops and LLM Ops practices including model registries version control evaluation benchmarks and monitoring
Experience working with large language models GenAI technologies vector databases or agent frameworks
Experience operating in a regulated environment and following GxP or similar compliance processes
Willingness and ability to travel domestically and internationally
Physical Requirements
This role involves regular standing walking sitting and the use of hands for handling or operating equipment. The employee may also need to reach climb balance stoop kneel crouch and maintain visual verbal and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds. This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.
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