Staff Principal Engineer Jobs

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ Remote: This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. About The Team The Commerce Site Reliability Engineering team is responsible for the reliability, scalability, and day-to-day operation of the platforms that power GoDaddy's Commerce ecosystem. We build and operate shared infrastructure, support critical production systems, and partner closely with engineering teams to ensure services remain secure, resilient, and highly available. As a Senior Site Reliability Engineer, you'll join a team that values ownership, operational excellence, and continuous improvement. Engineers are empowered to identify problems, drive meaningful change, and influence how reliability is delivered across the broader Commerce organisation. From improving operational maturity and reducing toil to modernising delivery platforms and strengthening incident response practices, this team plays a key role in enabling engineering teams to move quickly and safely. You'll work closely with engineers across infrastructure, cloud, security, networking, and application teams while helping shape the future of reliability engineering at GoDaddy. This role offers significant opportunity to broaden your impact, develop technical leadership skills, and grow toward Staff and Principal engineering positions over time. What you'll get to do... Lead reliability and operational improvement initiatives across GoDaddy's Commerce platform, helping engineering teams build and operate services safely and at scale. Own critical production systems, drive incident response and post-incident improvements, and continuously raise the bar

Principal/Staff Engineer, PCVD Film Deposition, TD — Fab 10N/X, Singapore. Apply via Workday.

Principal / Staff Engineer, Embedded Security, Firmware Development (SSD) — MSB, Singapore. Apply via Workday.

Principal/Staff Engineer, Process Integration, NTI NAND — Fab 10N/X, Singapore. Apply via Workday.

Principal/Staff Engineer Engineer, APTD CEM - Advanced Packaging Die Level Technology Engineering — Fab 10A, Singapore. Apply via Workday.

Principal/Staff Engineer, FE OCT TIQ — Taoyuan - Fab 11, Taiwan. Apply via Workday.

Staff/Principal Automation Integration Engineer — 2 Locations. Apply via Workday.

Principal/Staff Engineer, FE OCT Materials Cost — 2 Locations. Apply via Workday.

Principal/Staff Engineer, Frontend Operations Central Team Materials Cost — Hiroshima - Fab 15, Japan. Apply via Workday.

Principal/Staff Engineer, FE OCT Materials Cost — Fab 10A, Singapore. Apply via Workday.

Principal/Staff Engineer, FE OCT TIQ — Fab 10A, Singapore. Apply via Workday.

Lead Staff Engineer / Lead Principal Engineer PD SG Diffusion/Implant — Fab 10N/X, Singapore. Apply via Workday.

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

Senior/Staff/Principal Package Design Engineer — Boise, ID - Main Site. Apply via Workday.

FE CPIE PI Principal/Staff Engineer — 2 Locations. Apply via Workday.