Staff Machine Learning Engineer, MTS 2

eBay • Toronto, ON

54d

About The Position

At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts. Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet. Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all. About Our Team: The Product Knowledge team is at the epicenter of eBay’s Tech-driven, Customer-centric overhaul. Our team is responsible for building and leveraging eBay’s Product Knowledge, enabling a deep understanding of user intent and preferences. By transforming vast and complex data into actionable intelligence, we deliver personalized experiences across different stages of the buying and selling journey. Our team has a mix of highly proficient people from fields including Machine Learning, Data Science, Software Engineering, and Big Data Analytics. We have a strong culture of collaboration, and plenty of opportunity to learn, make an impact, and grow! The role: Staff ML Engineer We are seeking a seasoned ML Engineer who will serve as a technical leader within a high-impact, fast-moving team. This role is ideal for an engineer who brings clarity and direction to complex problem spaces, leads through influence, and partners effectively across disciplines. You will drive architectural decisions, elevate engineering quality, and unblock teams through deep technical expertise and strong collaboration.

Requirements

• MS or PhD in Computer Science, Statistics, Mathematics, or a related field, or equivalent practical experience.
• 8+ years of experience in software design and development with strong fundamentals in data structures, algorithms, and system design.
• Demonstrated experience leading technical initiatives and influencing engineering direction without direct people management responsibility.
• Proven expertise in building, deploying, and maintaining machine learning pipelines and production services at scale.
• Strong analytical and problem-solving skills, with the ability to navigate ambiguity and drive clarity.
• Experience working in agile development environments with a strong commitment to high engineering standards and operational excellence.
• Ability to proactively execute, break down complex problems, and guide others through technical decision-making.
• Excellent communication and interpersonal skills, with a collaborative mindset and appreciation for diverse perspectives.

Responsibilities

• Provide technical leadership across software and machine learning initiatives, influencing design, architecture, and long-term technical strategy.
• Define and drive short- and long-term technical direction, aligning engineering solutions with product and organizational goals.
• Design, implement, and optimize machine learning systems for search products, including model tuning, service performance, and data pipeline efficiency.
• Lead complex, multi-quarter technical projects, using business and system metrics to inform decisions and clearly communicate tradeoffs and outcomes to stakeholders.
• Own and evolve system architecture, proactively addressing technical debt while ensuring scalability, reliability, and alignment with the product roadmap.
• Establish and monitor key technical and delivery metrics to assess system health and engineering effectiveness.
• Multiply the impact of other engineers by providing mentorship, technical guidance, design reviews, and by enabling effective cross-team collaboration.
• Act as a role model for inclusive, collaborative engineering practices, fostering an environment where diverse perspectives are valued and engineers feel empowered to contribute.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level