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Lead Generative AI Architect
2 months ago
As a Senior AI Innovation Engineer at Madrigal Pharmaceuticals, you will play a pivotal role in harnessing cutting-edge AI technologies to foster advancements within the pharmaceutical sector. Your mission will be to develop business-oriented solutions that demonstrate the transformative potential of Large Language Models (LLMs) and spearhead the execution of our Generative AI strategy.
Key Responsibilities:
- Strategic Leadership:
- Formulate and oversee the Generative AI strategy.
- Pinpoint essential business challenges that can be addressed through Generative AI.
- Craft and execute strategies for the integration of Generative AI across the organization.
- Facilitate peer discussions and leverage quantitative analysis to positively influence decision-making.
- Architectural Design:
- Ensure the appropriate complexity of LLMs for diverse applications (e.g., selecting between Dolly and GPT-4).
- Establish technical standards and frameworks for Generative AI implementations.
- Lead efforts in prompt engineering to enhance LLM efficacy.
- Rapidly prototype and evaluate LLM applications to improve user experiences.
- Data Science and Machine Learning:
- Possess a robust theoretical foundation and extensive experience in machine learning, deep learning, and generative AI.
- Drive the fine-tuning of LLMs and the development of Retrieval-Augmented Generation (RAG) systems.
- Implement automated processes for predictive model validation and deployment.
- Enhance the AI/ML ecosystem, including Feature Stores and Model Stores, to maximize LLM utility.
- Contribute significantly to discussions on emerging machine learning techniques.
- Collaborative Engagement:
- Collaborate with interdisciplinary teams, including data scientists and research experts, to deliver features iteratively.
- Guide both internal and external developers in executing the Generative AI strategy.
- Engage with subject matter experts across various business domains.
- Educate technical and business stakeholders on the applications of Generative AI.
- Continuous Improvement:
- Exhibit a blend of business acumen, analytical prowess, and programming expertise to rapidly iterate through project hypotheses.
- Communicate findings effectively through structured reporting and presentations.
- Stay abreast of the latest developments in Large Language Models (LLMs) and their application in business contexts.
- Advanced degree (Ph.D. preferred) in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, or a related quantitative discipline.
- Over 10 years of experience with programming languages such as Python, SQL, R, MATLAB, and frameworks like PyTorch and Keras.
- 8+ years of expertise in machine learning and deep learning, including practical experience with LLM fine-tuning.
- 8+ years in data visualization and developing dashboards/web applications using Python and R tools.
- 8+ years in data manipulation and integration, with proficiency in complex queries and data product creation.
- 8+ years of experience in deploying AI/ML systems on platforms like Databricks or Dataiku.
- Strong knowledge of cloud-based data technologies (e.g., AWS, Azure, Google Cloud) for building scalable analytics solutions.
- Proven track record in machine learning and software engineering best practices.
- Demonstrated ability to articulate research findings through documentation and presentations.
- Fluency in English.
The base salary is determined by various factors, including the candidate's qualifications, skills, education, experience, business needs, and market conditions. The role may also be eligible for bonuses, equity, and comprehensive benefits, including flexible paid time off (PTO), medical, dental, vision, and life and disability insurance.
Madrigal is an Equal Opportunity Employer. All employment decisions are based on qualifications, merit, and business needs. Applicants will be considered for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, protected veteran status, or any other characteristic protected by applicable law.
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