Senior Machine Learning Engineering (Remote)

IQVIA•Durham, NC

1d•$108,000 - $270,000•Remote

About The Position

As one of our Senior Machine Learning Engineers, you will lead the design and development of ML applications across our product portfolio, with a strong focus on generative AI and large language model (LLM) solutions. You will be a hands-on technical leader, providing architecture and shaping coding standards. You will evangelize best practices for software engineering including design, development, and lifecycle maintenance, and will partner with multiple software engineering teams to encourage practices like code reusability, shared libraries, UX-driven design, and a culture of continuous improvement. You will help guide the transformation of machine learning research domain expertise in the areas of human data into viable prototypes. Your technical leadership will enable our Machine Learning Engineers to build and train new production-grade algorithms that can learn from complex, high-dimensional data to uncover patterns from which machine learning models and applications can be developed. Your ability to research current and emerging industry tools, techniques, and algorithms, and share these findings with colleagues will prove invaluable to your team's success. You will meet frequently with stakeholders, product managers, engineering managers, data scientists, and other individual contributor engineers to understand a wide array of technical and business impacting variables and distill these into strategic and tactical choices that our Machine Learning Engineering teams will use to develop and improve software products for our customers. Along with your primary directive of working across the product portfolio to support multiple scrum teams, you will also be expected to work with external customers either as a consultant or as a solution Machine Learning Engineer. There will also be opportunities to prepare and submit conference and journal articles.

Requirements

Familiarity with traditional ML algorithms (classification, regression) and MLOps processes
Experience with building, testing, measuring, and deploying machine learning models in production
Experience with LLM engineering, including: - Fine-tuning foundation models (GPT-4, Claude, open-source LLMs) - Implementing Retrieval-Augmented Generation (RAG) systems - Prompt engineering and LLM evaluation frameworks
Expertise in building generative AI applications: - Development of multimodal AI solutions (text, image) - Working with vector databases and embedding models - Context window optimization and token management
Prior engineering project leadership using relevant skills and technologies: - Python (Scikit-learn, TensorFlow, PyTorch, Pandas, Numpy, Scipy) - SQL, Linux/Mac command-line tools
Familiarity with agile software development lifecycle (SCRUM, Kanban, etc.)
Previous experience of owning, maintaining, and enhancing software data products
Attention to clarity of code, ease of development, and correctness of implementations
Good knowledge of software development best practices including testing, continuous integration, and DevOps tools
Experience with mentoring and training junior team members, especially pair programming
STEM-related degree (Bachelor's, Master's or Doctorate)
5-8 years' experience working on creating machine learning algorithms for production purposes

Nice To Haves

Advanced LLM infrastructure experience: - Orchestration frameworks for complex LLM workflows - Model quantization and optimization techniques - Experience implementing model guardrails and safety mechanisms
Responsible AI implementation: - Hallucination mitigation strategies - Evaluation frameworks for generative model outputs - Bias detection and mitigation techniques
Experience with emerging architectural approaches (mixture of experts, agent frameworks)
Knowledge of model distillation and efficient fine-tuning methods
Experience with clinical domain and with regulated data
Experience with large language models for healthcare applications
Knowledge of cloud systems such as AWS, Azure, GCP and containerization such as Docker
Experience working with large, real-world datasets
Demonstrated in-depth understanding of 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/healthcare technology
Knowledge of UX principles
Prior management training preferred but not required

Responsibilities

Lead the design and development of ML applications across our product portfolio, with a strong focus on generative AI and large language model (LLM) solutions.
Be a hands-on technical leader, providing architecture and shaping coding standards.
Evangelize best practices for software engineering including design, development, and lifecycle maintenance
Partner with multiple software engineering teams to encourage practices like code reusability, shared libraries, UX-driven design, and a culture of continuous improvement.
Help guide the transformation of machine learning research domain expertise in the areas of human data into viable prototypes.
Enable Machine Learning Engineers to build and train new production-grade algorithms that can learn from complex, high-dimensional data to uncover patterns from which machine learning models and applications can be developed.
Research current and emerging industry tools, techniques, and algorithms, and share these findings with colleagues.
Meet frequently with stakeholders, product managers, engineering managers, data scientists, and other individual contributor engineers to understand a wide array of technical and business impacting variables and distill these into strategic and tactical choices that our Machine Learning Engineering teams will use to develop and improve software products for our customers.
Work across the product portfolio to support multiple scrum teams
Work with external customers either as a consultant or as a solution Machine Learning Engineer.
Prepare and submit conference and journal articles.