Principal Generative AI Engineer
1 month ago
Position Responsibilities:
- Technical Leadership and Strategy:
- Develop and manage the Generative AI roadmap.
- Identify critical business problems that can be solved using Generative AI.
- Define and implement strategies for leveraging Generative AI within the organization.
- Lead discussions in peer reviews and use quantitative skills to influence decision-making positively.
- Solution Architecture and Design:
- Ensure the appropriate level of LLM complexity for various use cases (e.g., Dolly vs. GPT-4).
- Create technical standards and blueprints for Generative AI scenarios.
- Lead prompt engineering efforts to optimize LLM performance.
- Quickly prototype and test LLM scenarios to refine user experiences.
- Advanced Analytics, Data Science, and Machine Learning:
- Strong theoretical background and extensive experience in machine/deep learning, generative AI, and statistical modeling.
- Spearhead fine-tuning of LLMs and building RAG (Retrieval-Augmented Generation) systems.
- Develop and embed automated processes for predictive model validation, deployment, and implementation.
- Influence the AI/ML stack, including Feature Stores, Model Stores, and automated MLOps, to maximize the value of LLMs.
- Make impactful contributions to internal discussions on emerging machine learning methodologies.
- Cross-Functional Collaboration:
- Work with cross-functional teams, including data scientists, data engineers, and research scientists, to deliver features iteratively.
- Lead internal and external developers to execute the Generative AI roadmap.
- Connect and collaborate with subject matter experts across different business areas.
- Educate technical and business leaders on the use of Generative AI.
- Continuous Learning and Innovation:
- Demonstrate a combination of business focus, strong analytical and problem-solving skills, and programming knowledge to quickly cycle hypotheses through the discovery phase of projects.
- Report findings clearly and structurally through excellent written and communication skills.
- Stay updated with the latest advancements in Large Language Models (LLMs) and apply them to business scenarios.
- Advanced degree (Ph.D. preferred) in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics, Bioinformatics, or a related quantitative field.
- 10+ years of proficiency in Python, SQL, R, MATLAB, PyTorch, Keras, and git.
- 8+ years of experience in ML/deep learning, including hands-on experience with LLM fine-tuning and/or training (e.g., ChatGPT, BERT, Bard, LLaMA, Dolly).
- 8+ years of experience in data visualization and creating dashboards/web applications using Python and R-based tools (Dash, Streamlit, Shiny).
- 8+ years of experience in data manipulation, integration, writing complex queries, and creating data products.
- 8+ years of implementing AI/ML systems using platforms like Databricks or Dataiku.
- Strong understanding of cloud-based data platforms and technologies (e.g., AWS, Azure, Google Cloud) and their application in building scalable and efficient analytics solutions.
- Proven experience in machine learning and software engineering best practices.
- Demonstrated ability in writing and presenting papers, documentation, and presentations to explain research findings.
- Fluency in English.
Base salary is determined by several factors that include, but are not limited to, a successful candidate's qualifications, skills, education, experience, business needs, and market demands. The role may also be eligible for bonus, equity, and comprehensive benefits, which include flexible paid time off (PTO), medical, dental, vision, and life and disability insurance.
Madrigal is an Equal Opportunity Employer. All employment is decided on the basis of qualifications, merit, and business need. Applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex gender identity, sexual orientation, national origin, age, disability, protected veteran or disabled status, or other characteristic protected by applicable federal, state, or local law.
Unsolicited resumes from agencies should not be forwarded to Madrigal. Madrigal will not be responsible for any fees arising from the use of resumes through this source. Madrigal will only pay a fee to agencies if a formal agreement between Madrigal and the agency has been established.
Please be aware that we are currently receiving numerous reports of individuals misrepresenting themselves as Madrigal Pharmaceuticals’ Hiring Managers, seeking to engage with job candidates through fraudulent online advertisements or job posting sites. These unauthorized individuals are using Madrigal’s name and logo in an attempt to solicit up-front fees and obtain personal information from interested job candidates. Please know that Madrigal does not conduct interviews via text or in chat rooms; conduct interviews via Skype, RingCentral or solely via telephone; charge candidates an advance fee of any kind (e.g., fees for purchasing equipment); nor does it offer positions of employment without undergoing a thorough recruiting process. Interviews with Madrigal are conducted via the Zoom platform.
Please also note that any correspondence with regard to employment would come from an authorized madrigalpharma.com email address or from an email address from one of our trusted search firm partners. We are aware that incorrect/fraudulent email addresses, with Madrigal misspelled, have been utilized in these most recent fraud attempts. If you receive unsolicited employment offers from people claiming to work for Madrigal we recommend that you: do not respond to their questions; do not open any attachments; and do not click on any hyperlinks.
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