Base Salary
$111k - $279k/yr
Responsibilities
- Lead the design and development of machine learning and generative AI applications across the product portfolio.
- Build, train, test, measure, and deploy production-grade machine learning models and algorithms.
- Develop LLM solutions including foundation-model fine-tuning, RAG systems, prompt engineering, and LLM evaluation.
- Create multimodal AI applications using text and image data, vector databases, embedding models, and context/token optimization.
- Provide hands-on architecture and technical leadership across multiple software engineering teams.
- Guide research-domain expertise in human data toward viable prototypes and production software products.
- Partner with stakeholders, product managers, engineering managers, data scientists, and engineers to make strategic and tactical technical decisions.
- Research emerging tools, techniques, algorithms, architectures, and responsible AI practices and share findings with colleagues.
- Own, maintain, and enhance software data products.
- Mentor and train junior team members, including through pair programming.
- Work with external customers as a consultant or solution machine learning engineer.
- Prepare and submit conference and journal articles when appropriate.
Requirements
- Bachelor's, Master's, or Doctorate degree in a STEM-related field.
- 5-8 years of experience creating machine learning algorithms for production purposes.
- Familiarity with traditional machine learning algorithms such as classification and regression and with MLOps processes.
- Experience building, testing, measuring, and deploying machine learning models in production.
- Experience fine-tuning foundation models including GPT-4, Claude, and open-source LLMs.
- Experience implementing RAG systems, prompt engineering, and LLM evaluation frameworks.
- Expertise in generative AI applications, multimodal AI, vector databases, embedding models, context-window optimization, and token management.
- Prior engineering project leadership using Python, Scikit-learn, TensorFlow, PyTorch, Pandas, Numpy, Scipy, SQL, and Linux or Mac command-line tools.
- Experience owning, maintaining, and enhancing software data products.
- Knowledge of software development best practices including testing, continuous integration, and DevOps tools.
- Experience mentoring and training junior team members, especially through pair programming.
- Preferred experience with LLM orchestration, model quantization and optimization, guardrails, safety mechanisms, hallucination mitigation, bias mitigation, model distillation, efficient fine-tuning, mixture-of-experts architectures, and agent frameworks.
- Preferred experience with clinical domains, regulated data, healthcare LLM applications, large real-world datasets, cloud systems, Docker, CI/CD tools, biostatistics, life sciences, healthcare technology, and UX principles.
- Prior management training is preferred but not required.
Benefits
- Remote/WFH work arrangement.
- Potential additional incentive plans, bonuses, and other compensation may be offered in addition to health and welfare benefits.
Tech Stack
Categories
About IQVIA
IQVIA (NYSE:IQV) is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. IQVIA’s portfolio of solutions are powered by IQVIA Connected Intelligence™ to deliver actionable insights and services built on high-quality health data, Healthcare-grade AI™, advanced analytics, the latest technologies and extensive domain expertise. With approximately 88,000 employees in over 100 countries, including experts in healthcare, life sciences, data science, technology and operational excellence, IQVIA is dedicated to accelerating the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. IQVIA is a global leader in protecting individual patient privacy. The company uses a wide variety of privacy-enhancing technologies and safeguards to protect individual privacy while generating and analyzing information on a scale that helps healthcare stakeholders identify disease patterns and correlate with the precise treatment path and therapy needed for better outcomes. IQVIA’s insights and execution capabilities help biotech, medical device and pharmaceutical companies, medical researchers, government agencies, payers and other healthcare stakeholders tap into a deeper understanding of diseases, human behaviors and scientific progress, in an effort to advance healthcare. To learn more, visit www.iqvia.com.