Job Description
Principal Machine Learning Engineer
United States
Full time
Principal Machine Learning Engineer
Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand-new methodologies, tools, statistical methods, and models. What’s more, we are in collaboration with leading academics, industry experts, and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.
Join us to do the best work of your career and make a profound social impact as a Principal Machine Learning Engineer in Round Rock, Texas, Hopkinton, Massachusetts or Remote United States (U.S.)
What you’ll achieve
As a Principal Machine Learning Engineer on a growing team, you will bring in your industry experience to drive software architecture and enterprise compute to support the development and productionization of machine-learning models at both technical and business scale.
You will:
- Collaborate with our Data Science, Machine Learning Operations (MLOps), Data Engineering, and IT teams to drive the technical roadmap and ensure world-class engineering practices
- Lead the training and productionization of machine-learning models at scale
- Implement new technologies and frameworks to solve customer-centric problems
- Support and mentor junior engineers
Take the first step toward your dream career
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:
Essential Requirements
- U.S. Citizen residing in the U.S.
- Bachelor’s Degree in Computer Science, Engineering, IT, or equivalent professional experience
- 8+ years of related professional software-engineering or ML-engineering experience in enterprise-level environments
- 6+ years’ experience with microservices software architecture and APIs and leading the end-to-end design and development of scalable services, including monitoring and production support
- Experience building scaled solutions with private cloud or on-premise IT infrastructure using open-source frameworks, DevOps practices, including software testing and CI/CD
Desired Requirements
- Experience working with container-based technologies, such as Docker
- Experience with Python machine-learning libraries (i.e. Scikit-learn, PyTorch, TensorFlow)
