Manager, AI Engineering

About the role

At Acadia, we're committed to advancing meaningful innovation in neurological and rare disease treatments. Our portfolio includes FDA-approved therapies for Parkinson’s disease psychosis and Rett syndrome, alongside a robust pipeline targeting Alzheimer’s disease psychosis, Lewy body dementia psychosis, and other underserved patient needs.

Responsibilities

• Design, develop, validate, and deploy scalable AI/ML and GenAI solutions addressing complex business problems and supporting enterprise priorities.
• Contribute to the 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 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 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.
• Support AI governance by supporting model documentation, lineage, risk assessment, bias testing, explainability, and compliance with applicable regulations and frameworks.
• Contribute to 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. 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.

Requirements

• Master’s degree or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative discipline, or equivalent practical experience.
• 5+ years of hands-on 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 scikit-learn, 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.

Qualifications

• Willingness and ability to travel domestically and internationally.

Skills

• Advanced proficiency in Python and common ML frameworks and tools such as scikit-learn, 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.

Benefits

US-based Employees: Competitive base, bonus, new hire and ongoing equity packages; Medical, dental, and vision insurance; Employer-paid life, disability, business travel and EAP coverage; 401(k) Plan with a fully vested company match 1:1 up to 5%; Employee Stock Purchase Plan with a 2-year purchase price lock-in; 15+ vacation days; 13 -15 paid holidays, including office closure between December 24th and January 1st; 10 days of paid sick time; Paid parental leave benefit; Tuition assistance.

Pay

$128,000—$160,200 USD

Schedule

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.