Associate Director, AI/ML Engineering

ACADIA Pharmaceuticals Inc.; Princeton (NJ); Hybrid; USD 159,000 - 199,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) Plan with company match

15+ vacation days

Job summary

ACADIA Pharmaceuticals Inc. is seeking an Associate Director of AI/ML Engineering to lead the design and deployment of Generative AI solutions. This role emphasizes a hands-on technical approach and collaboration with cross-functional teams.

Candidates should have a master's or PhD and at least 7 years in AI/ML engineering, including strong experience with multi-agent frameworks and generative technologies. The position offers a competitive salary and several attractive benefits.

Qualifications

• Minimum of 7 years in AI/ML engineering with 3 years in Generative AI.
• Experience building MCP servers and integrating AI systems with data sources.
• Strong experience in RAG pipeline development.

Responsibilities

• Design and deploy AI workflows that automate complex processes.
• Architect servers for enterprise tool integration.
• Evaluate AI system performance across various dimensions.

Skills

AI/ML engineering

Generative AI

multi-agent frameworks

Python

ML Ops

Education

Master's or PhD in Machine Learning, Computer Science, Data Science, or related field

Tools

PyTorch

TensorFlow

scikit-learn

Hugging Face

Job description

Location: San Diego, CA; South San Francisco, CA; or Princeton, NJ. Hybrid model requires in‑office work three days per week on average.

Position Summary

The Associate Director, AI/ML Engineering serves as a hands‑on technical leader driving the design, architecture, and delivery of Generative AI and agentic AI solutions across the enterprise. This role builds scalable multi‑agent systems, connects AI solutions to enterprise data and tools, and ensures safe, reliable deployment through robust evaluation and guardrail frameworks. The position also applies strong machine learning and foundation model expertise to deliver high‑impact use cases within a regulated biopharmaceutical environment.

Primary Responsibilities

• Design, build, and deploy agentic AI workflows that automate and transform complex business processes, leveraging multi‑agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or equivalent).
• Architect and implement MCP servers to expose enterprise tools, APIs, and data sources as standardized capabilities consumable by AI agents.
• Connect multi‑agent systems to enterprise databases, internal APIs, and MCP servers to enable grounded, context‑aware, and action‑oriented AI solutions.
• Partner cross‑functionally with internal teams to define data contracts, lineage standards, and quality thresholds required for AI/ML use cases.
• Design and implement agentic memory systems (short‑term, long‑term, episodic) and planning/reasoning loops to support reliable autonomous task execution.
• Evaluate agentic system performance across accuracy, reliability, latency, cost, and safety dimensions using structured benchmarks and red‑team methodologies.
• Build and maintain guardrail frameworks (input/output filtering, content moderation, policy enforcement, hallucination detection) to ensure the safety, compliance, and trustworthiness of GenAI and agentic solutions.
• Develop retrieval‑augmented generation (RAG) pipelines, including chunking strategies, embedding models, vector store selection, and retrieval optimization for enterprise knowledge bases.
• Apply prompt engineering, few‑shot learning, and fine‑tuning techniques to adapt foundation models for domain‑specific pharma use cases.
• Design, develop, validate, and deploy traditional machine learning models (classification, regression, clustering, time‑series, survival analysis) to address structured business problems.
• Build and maintain end‑to‑end ML pipelines adhering to LLM Ops / ML Ops standards including model registry, evaluation benchmarks, prompt/version control, observability, and rollback procedures.
• Experience in working with real‑world data (RWD), claims data, EHR data, clinical study data, translational and biological data and the corresponding databases is a plus.
• Other responsibilities as assigned.

Education, Experience and Skills

• Master’s or PhD in Machine Learning, Computer Science, Data Science, Information Systems, or a related quantitative discipline.
• Minimum of 7 years of experience in AI/ML engineering, including at least 3 years of hands‑on experience with Generative AI and agentic AI systems.
• Expertise in multi‑agent frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar technologies.
• Experience building MCP servers and integrating AI systems with enterprise data sources, APIs, and tools.
• Strong experience in RAG pipeline development, embedding models, and vector database technologies.
• Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, scikit‑learn, and Hugging Face.
• Experience implementing ML Ops or LLM Ops practices, including model lifecycle management, evaluation, and deployment.
• Ability to travel domestically and internationally as required.

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.

Salary Range

$159,000—$199,000 USD

Benefits

• 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.

EEO Statement

Studies have shown that women and people of color are less likely to apply for jobs unless they believe they meet every one of the qualifications in the exact way they are described in job postings. We are committed to building a diverse, equitable, inclusive, and innovative company, and we are looking for the BEST candidate for the job. That candidate may be one who comes from a less traditional background or may meet the qualifications in a different way. We strongly encourage you to apply, especially if the reason you are the best candidate isn’t exactly what we describe here.

It is the policy of Acadia to provide equal employment opportunities to all employees and employment applicants without regard to considerations of race, including related to hairstyle, color, religion or religious creed, sexual orientation, gender, gender identity, gender expression, gender transition, country of origin, ancestry, citizenship, age, physical or mental disability, genetic information, legally‑protected medical condition or information, marital status, domestic partner status, family care status, military caregiver status, veteran or military status (including reserve status, National Guard status, and military service or obligation), status as a victim of domestic violence, sexual assault or stalking, enrollment in a public assistance program, or any basis protected under federal, state or local law.

We are an equal opportunity employer. If you are a qualified individual with a disability or a disabled veteran, you have the right to request a reasonable accommodation.