Senior Data Engineer

About the Job

The Red Hat Products & Global Engineering Business Insights team is looking for a Principal Machine Learning Engineer to join us in Raleigh, NC or Boston, MA. In this role, you will serve in the Business Unit organization which spans Red Hat’s product portfolio. You’ll work closely with a team of data scientists, data engineers, and stakeholders to operationalize machine learning and generative AI models related to product development and customer experience. Some of our current production-ready models include gradient boosting, transformer-based LLM, deep learning, and logistic regression models.

What You Will Do

• Collaborate with team members to develop and operationalize data science solutions, including migrating prototypes (e.g. Jupyter Notebooks) into production environments

• Accelerate data workflows and model training using distributed computing 

• Lead the end-to-end ML product lifecycle, from requirements gathering to validation, implementation, deployment, and post-deployment

• Work closely with data engineering and MLOps functional roles to operationalize scalable data science solutions through automation and continuous delivery

• Engage with stakeholders to improve ML systems design and application development

• Establish CI/CD and unit testing practices for model development

• Work closely with data scientists to determine appropriate model performance and data/concept drift monitoring

• Lead and guide the team to implement MLOps best practices

What You Will Bring

• Bachelor's degree in mathematics, statistics, computer science, or a related technical field, or equivalent work experience (master’s degree a plus)

• 5+ years of experience developing production-grade machine learning models

• 2+ years of experience with Python, containers, kubernetes and CI/CD 

• Experience querying/transforming structured/unstructured data (SQL, PySpark, Scala)

• Proven experience with a deep learning framework (PyTorch, TensorFlow, Keras)

• Strong theoretical knowledge and applied experience of statistics, machine learning and large language models and algorithms (unsupervised and supervised)

• Demonstrated ability to produce well-documented, well-formatted code using object-oriented design principles

• Proficient with CI/CD, containerized development, version control (e.g. Docker, Jenkins)

Preferred Skills

• Integration of ML tracking and orchestration tools (e.g. Airflow, MLflow, Kubeflow)

• Experience with deploying large language models, specifically RAG solutions 

• Experience with cloud-native technologies, specifically Red Hat OpenShift Container Platform

• Experience with distributed computing (e.g. Dask, Ray)

• Ability to fine tune deployed models to improve scalability, reliability, and performance

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal …