Associate Director, AI/ML Engineering
Position Summary
This position is based in San Diego, CA, South San Francisco, CA, or Princeton, NJ. Acadia's hybrid model requires this role to work in the office three days per week on average.
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).
- Arcitect 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-teaming 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.
Education/Experience/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
- Regular standing, walking, sitting, and the use of hands for handling or operating equipment
- 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
- Occasionally lift and/or move up to 20 pounds
What we offer 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
EEO Statement (US-based Employees)
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.
Additional Information
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.
If you are a qualified individual with a disability or a disabled veteran, you have the right to request a reasonable accommodation. Furthermore, you may request additional support if you are unable or limited in your ability to use or access Acadia’s career website due to your disability, along with any accommodations throughout the interview process. To request or inquire about your reasonable accommodation, please complete our Reasonable Accommodation Request Form or contact us at talentacquisition@acadia-pharm.com or 858-261-2923.
Please note that reasonable accommodations granted throughout the recruiting process are not guaranteed to be the same accommodations given if hired. A new request will need to be submitted for any ADA accommodations after starting employment.