Senior Manager, AI Engineering

Scorpion Therapeutics; South San Francisco (CA); On-site; USD 150,000 - 188,000; Full time

Benefits offered by this job

Discretionary bonus and equity awards

Medical/dental/vision

401(k) match 1:1 up to 5%

Employee Stock Purchase Plan

15+ vacation days

13–15 paid holidays

Tuition assistance

Job summary

Scorpion Therapeutics is seeking a Senior Manager, AI Engineering to advance enterprise AI capabilities across R&D, Commercial, and Corporate functions. You will lead the design, deployment, and governance of scalable AI/ML solutions, partnering with stakeholders to translate data into actionable insights and business value.

Lead AI governance, model risk, lifecycle management, and responsible AI initiatives while driving GxP alignment and regulated-environment readiness across platforms and

Qualifications

• MS in a quantitative field with 5+ years experience in ML/AI/data science.
• PhD with 2+ years industry (or equivalent research) in ML/AI/data science.
• Experience deploying ML/AI in production or research.

Responsibilities

• Execute enterprise AI strategy/roadmap; align AI/ML initiatives to business priorities; identify high-value use cases.
• Develop and deliver AI/ML solutions and analytics/data science use cases supporting data-driven decisions.
• Provide technical expertise for AI governance (model risk, responsible AI, lifecycle management).
• Assess feasibility, business value, and implementation risks to support prioritization/investment decisions.
• Design, develop, validate, deploy, and support ML models and scalable ML/LLM pipelines using ML Ops/LLM Ops.
• Evaluate/optimize GenAI per enterprise architecture.
• Maintain documentation (model/prompt/dataset) for lineage, auditability, approvals, and system-of-record compliance.
• Create reusable frameworks/standards to accelerate adoption, scalability, and operational efficiency.
• Partner with IT, Data Insights & Analytics, and Information Security on platforms, infrastructure, vendor/RFI/RFP.
• Apply responsible AI standards (bias/robustness, explainability, human oversight, incident response, regulatory compliance).
• Support GxP and evolving AI regulation alignment (e.g., NIST AI RMF, EU AI Act readiness).

Skills

Python

SQL

PyTorch

TensorFlow

scikit-learn

GenAI

ML Ops

Responsible AI

Education

MS in a quantitative field

PhD with 2+ years in ML/AI

Job description

Senior Manager, AI Engineering—advance Acadia’s enterprise AI capabilities through development, deployment, governance of scalable AI/ML solutions. Partner with R&D, Commercial, and Corporate stakeholders to translate data into actionable insights and business value.

Primary Responsibilities

• Execute enterprise AI strategy/roadmap; align AI/ML initiatives to business priorities; identify high-value use cases
• Develop and deliver AI/ML solutions and analytics/data science use cases supporting data-driven decisions
• Provide technical expertise for AI governance (model risk, responsible AI, lifecycle management)
• Assess feasibility, business value, and implementation risks to support prioritization/investment decisions
• Design, develop, validate, deploy, and support ML models and scalable ML/LLM pipelines using ML Ops/LLM Ops
• Evaluate/optimize GenAI (LLMs, vector databases, endpoints, agent frameworks, guardrails) per enterprise architecture
• Maintain documentation (model/prompt/dataset) for lineage, auditability, approvals, and system-of-record compliance
• Create reusable frameworks/standards to accelerate adoption, scalability, and operational efficiency
• Partner with IT, Data Insights & Analytics, and Information Security on platforms, infrastructure, vendor/RFI/RFP
• Apply responsible AI standards (bias/robustness, explainability, human oversight, incident response, regulatory compliance)
• Support GxP and evolving AI regulation alignment (e.g., NIST AI RMF, EU AI Act readiness)

Education/Experience/Skills

• MS in a quantitative field with 5+ years experience, or PhD with 2+ years industry (or equivalent research) in ML/AI/data science
• Experience deploying/supporting ML/AI in production or research
• Proficiency in Python, SQL; PyTorch/TensorFlow/scikit-learn
• GenAI experience (LLMs, RAG, vector databases, agent frameworks)
• ML Ops/LLM Ops (version control, evaluation, monitoring, deployment)
• Knowledge of responsible AI, explainability, evaluation, and AI governance; regulated environments preferred
• Domestic/international travel as needed

Benefits

• Discretionary bonus and equity awards; $150,300—$187,900 salary range
• Medical/dental/vision; employer-paid life/disability/business travel/EAP; 401(k) match 1:1 up to 5%; Employee Stock Purchase Plan; 15+ vacation days; 13–15 paid holidays; paid sick time; paid parental leave; tuition assistance