Associate Director, AI/ML Engineering
Acadia Pharmaceuticals
August 06, 2026
Remote friendly (Princeton, NJ)
United States
IT
Position Summary
Associate Director, AI/ML Engineering—hands-on technical leader for Generative AI and agentic AI solutions in a regulated biopharmaceutical environment.
Primary Responsibilities
- Design, build, and deploy agentic AI workflows using multi-agent orchestration (e.g., LangGraph, AutoGen, CrewAI).
- Architect and implement MCP servers to expose enterprise tools/APIs/data as standardized AI capabilities.
- Integrate multi-agent systems with enterprise databases, internal APIs, and MCP servers for grounded, context-aware, action-oriented solutions.
- Define data contracts, lineage standards, and quality thresholds with cross-functional teams.
- Build agentic memory (short-/long-term/episodic) and planning/reasoning loops for reliable autonomous execution.
- Evaluate performance (accuracy, reliability, latency, cost, safety) using benchmarks and red-teaming.
- Build guardrail frameworks (filtering, moderation, policy enforcement, hallucination detection).
- Develop RAG pipelines (chunking, embeddings, vector store selection, retrieval optimization).
- Use prompt engineering, few-shot learning, and fine-tuning for domain-specific pharma use cases.
- Develop and deploy ML models (classification, regression, clustering, time-series, survival analysis).
- Maintain end-to-end ML/LLM Ops pipelines (model registry, evaluation, prompt/version control, observability, rollback).
Education/Experience/Skills
- Master’s or PhD in ML/CS/Data Science/IS or related quantitative field.
- 7+ years AI/ML engineering; 3+ years hands-on Generative AI/agentic AI.
- Expertise with multi-agent frameworks; experience building MCP servers.
- Strong RAG/embeddings/vector DB experience.
- Proficient in Python; PyTorch/TensorFlow/scikit-learn/Hugging Face.
- Experience with ML Ops/LLM Ops; domestic/international travel as required.
- Real-world data (RWD, claims, EHR, Clinical Study, translational/biological) is a plus.
Compensation/Benefits (selected)
- Salary range: $172,000–$215,000 USD.
- Eligible for discretionary bonus and equity.
- Medical/dental/vision; 401(k) match; paid vacation/holidays/sick time; paid parental leave; tuition assistance.
Physical Requirements
- Regular office activity; occasional lifting up to 20 lbs; ability to travel overnight and work after hours as needed.
Associate Director, AI/ML Engineering—hands-on technical leader for Generative AI and agentic AI solutions in a regulated biopharmaceutical environment.
Primary Responsibilities
- Design, build, and deploy agentic AI workflows using multi-agent orchestration (e.g., LangGraph, AutoGen, CrewAI).
- Architect and implement MCP servers to expose enterprise tools/APIs/data as standardized AI capabilities.
- Integrate multi-agent systems with enterprise databases, internal APIs, and MCP servers for grounded, context-aware, action-oriented solutions.
- Define data contracts, lineage standards, and quality thresholds with cross-functional teams.
- Build agentic memory (short-/long-term/episodic) and planning/reasoning loops for reliable autonomous execution.
- Evaluate performance (accuracy, reliability, latency, cost, safety) using benchmarks and red-teaming.
- Build guardrail frameworks (filtering, moderation, policy enforcement, hallucination detection).
- Develop RAG pipelines (chunking, embeddings, vector store selection, retrieval optimization).
- Use prompt engineering, few-shot learning, and fine-tuning for domain-specific pharma use cases.
- Develop and deploy ML models (classification, regression, clustering, time-series, survival analysis).
- Maintain end-to-end ML/LLM Ops pipelines (model registry, evaluation, prompt/version control, observability, rollback).
Education/Experience/Skills
- Master’s or PhD in ML/CS/Data Science/IS or related quantitative field.
- 7+ years AI/ML engineering; 3+ years hands-on Generative AI/agentic AI.
- Expertise with multi-agent frameworks; experience building MCP servers.
- Strong RAG/embeddings/vector DB experience.
- Proficient in Python; PyTorch/TensorFlow/scikit-learn/Hugging Face.
- Experience with ML Ops/LLM Ops; domestic/international travel as required.
- Real-world data (RWD, claims, EHR, Clinical Study, translational/biological) is a plus.
Compensation/Benefits (selected)
- Salary range: $172,000–$215,000 USD.
- Eligible for discretionary bonus and equity.
- Medical/dental/vision; 401(k) match; paid vacation/holidays/sick time; paid parental leave; tuition assistance.
Physical Requirements
- Regular office activity; occasional lifting up to 20 lbs; ability to travel overnight and work after hours as needed.