Senior Machine Learning Engineer, Analytics Center of Excellence (Remote/WFH)
About The Position
The Senior Machine Learning Engineer will lead the design and development of machine learning applications across IQVIA’s product portfolio, with a strong focus on generative AI and large language model solutions. This hands-on technical leader provides architectural guidance, shapes coding standards, promotes software engineering best practices, and partners with software engineering teams to encourage reusable code, shared libraries, UX-driven design, and continuous improvement. The role guides the transformation of machine learning research expertise in human data into viable prototypes and helps Machine Learning Engineers build and train production-grade algorithms for complex, high-dimensional data. It involves researching emerging tools, techniques, and algorithms and sharing findings with colleagues. The engineer works frequently with stakeholders, product managers, engineering managers, data scientists, and other engineers to translate technical and business considerations into strategic and tactical choices for software products. The position supports multiple scrum teams across the product portfolio and may involve working with external customers as a consultant or solution Machine Learning Engineer. There may also be opportunities to prepare and submit conference and journal articles.
Requirements
- Familiarity with traditional machine learning algorithms, including classification and regression, and MLOps processes.
- Experience building, testing, measuring, and deploying machine learning models in production.
- Experience with LLM engineering, including fine-tuning foundation models such as GPT-4, Claude, and open-source LLMs; implementing RAG systems; and prompt engineering and LLM evaluation frameworks.
- Expertise developing generative AI applications, including multimodal text and image solutions, vector databases and embedding models, context-window optimization, and token management.
- Prior engineering project leadership using relevant technologies.
- Experience with Python and libraries including Scikit-learn, TensorFlow, PyTorch, Pandas, Numpy, and Scipy.
- Experience with SQL and Linux or Mac command-line tools.
- Familiarity with agile software development lifecycles, such as SCRUM and Kanban.
- Previous experience owning, maintaining, and enhancing software data products.
- Attention to code clarity, ease of development, and correctness of implementations.
- Good knowledge of software development best practices, including testing, continuous integration, and DevOps tools.
- Experience mentoring and training junior team members, especially through pair programming.
- A STEM-related bachelor's, master's, or doctoral degree.
- 5–8 years of experience creating machine learning algorithms for production purposes.
Nice To Haves
- Advanced LLM infrastructure experience, including orchestration frameworks for complex LLM workflows, model quantization and optimization, and guardrails and safety mechanisms.
- Responsible AI implementation experience, including hallucination mitigation, generative model output evaluation, and bias detection and mitigation.
- Experience with emerging architectural approaches such as mixture of experts and agent frameworks.
- Knowledge of model distillation and efficient fine-tuning methods.
- Experience in clinical domains and with regulated data.
- Experience with LLMs for healthcare applications.
- Knowledge of cloud systems such as AWS, Azure, or GCP and containerization such as Docker.
- Experience working with large, real-world datasets.
- Demonstrated in-depth understanding of the product development lifecycle.
- Demonstrated aptitude for and interest in peer mentorship.
- Experience deploying code into production through CI/CD tools.
- Knowledge of biostatistics, life sciences, or healthcare technology.
- Knowledge of UX principles.
- Prior management training.
Responsibilities
- Lead the design and development of machine learning applications across the product portfolio, focusing particularly on generative AI and LLM solutions.
- Provide hands-on technical leadership, architecture guidance, and direction for coding standards.
- Promote software engineering best practices across design, development, and lifecycle maintenance.
- Partner with software engineering teams to encourage code reuse, shared libraries, UX-driven design, and continuous improvement.
- Guide the transformation of machine learning research expertise in human data into viable prototypes.
- Enable Machine Learning Engineers to build and train production-grade algorithms for complex, high-dimensional data.
- Research current and emerging industry tools, techniques, and algorithms, and share findings with colleagues.
- Meet with stakeholders, product managers, engineering managers, data scientists, and engineers to understand technical and business considerations and turn them into strategic and tactical choices.
- Support multiple scrum teams in developing and improving customer-facing software products.
- Work with external customers as a consultant or solution Machine Learning Engineer.
- Prepare and submit conference and journal articles as opportunities arise.
- Mentor and train junior team members, including through pair programming.
Benefits
- Health and welfare benefits may be offered, depending on the position.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
