Senior Applied Researcher

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 the team and the role: The AI Systems Performance & Governance team at eBay AI, Research and Innovation is looking for a highly qualified Senior Applied Researcher to join our team in Toronto. In this role, you will work at the intersection of applied research and AI governance for Generative AI systems (LLMs, VLMs, and agentic systems). You will focus on the science of evaluation, monitoring, and safety for GenAI applications, while contributing to the development of AI sandbox environments, evaluation frameworks, and governance best practices. You will help ensure that GenAI and agentic systems are scientifically grounded, properly evaluated, safe, and production-ready across their full lifecycle. What you will accomplish: Drive the fundamental science behind evaluation, creating robust methodologies and metrics to accurately assess the performance, safety, and reliability of LLMs, VLMs, and agentic systems, including offline metrics, human evaluation, and online experimentation. Define scientifically grounded metrics for complex GenAI systems, including RAG pipelines and multi-agent workflows (e.g., hallucination, grounding, robustness, agent reliability, safety). Provide scientific leadership across complex and ambiguous GenAI initiatives by setting research direction, reviewing evaluation and safety methodologies, and driving alignment on technical standards across teams. Build and evolve AI Sandbox environments for safe experimentation, benchmarking, and validation of GenAI and agentic systems. Advance the science behind building content moderation and safety guardrails, developing novel approaches for agentic safety steering to ensure autonomous and generative systems operate safely and ethically. Establish scientific best practices and anti-patterns for GenAI and agentic application development, covering evaluation, safety, and system design. Partner with engineering and product teams to ensure evaluation, safety, and monitoring approaches are applied consistently in production systems. Translate Responsible AI requirements into measurable, testable, and scalable evaluation and safety solutions. What you will bring: Master’s degree or PhD in Computer Science, Engineering, Mathematics, or a related field. Proven experience in machine learning, with strong hands-on experience building at least one of the following: LLMs, VLMs, Conversational Search systems, Agentic Systems, or Content Moderation solutions. Proficiency in Python and frameworks such as PyTorch, TensorFlow, Langfuse, LangGraph, or similar. Solid understanding of machine learning algorithms, model architectures, training techniques, and building performant inference pipelines. Experience with model inference optimization techniques and libraries is a plus. Experience with data preprocessing, feature engineering, model evaluation metrics, and large-scale data processing frameworks such as Spark. Solid understanding of the ML lifecycle, including experimentation, validation, and post-deployment monitoring. Excellent analytical and problem-solving skills, and the ability to work in a fast-paced, dynamic environment. Demonstrated experience independently leading complex applied research initiatives from problem formulation through production adoption, with evidence of influencing technical direction, mentoring others, and establishing methodologies or standards used beyond an individual project. Strong communication and collaboration skills, with the ability to explain complex technical concepts to non-technical collaborators, propose creative solutions, and support tracking and delivery within release plans. Publication record in top AI conferences or journals is a strong plus. Experience with AI safety, LLM/VLM/agent guards, content moderation, and policy-driven GenAI evaluation is a strong plus. What We Offer An opportunity to work on cutting-edge research in GenAI evaluation and monitoring, making significant contributions to both the field and real-world applications. A collaborative and supportive work environment where innovation and creativity are encouraged. Access to state-of-the-art resources and tools to support your research and development work. A culture that values diversity, inclusion, and the professional growth of its members. Competitive compensation and benefits package, tailored to attract the best talent in the field. Additional Details This job posting relates to an existing vacancy within eBay. eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at [email protected]. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility. 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You will drive the fundamental science behind evaluation, monitoring, and safety for Generative AI systems including LLMs and agentic workflows. You will also partner with engineering and product teams to establish scientific best practices and ensure AI solutions are production-ready.

Candidates must hold a Master's degree or PhD in Computer Science, Engineering, Mathematics, or a related field. You need proven experience in machine learning and hands-on expertise with LLMs, VLMs, or agentic systems, along with proficiency in Python and relevant AI frameworks.

• Competitive compensation • Professional growth opportunities • Supportive work environment • State-of-the-art resources

• Machine learningPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Machine learning
• LLMs
• VLMs
• Agentic systems
• Python
• PyTorch
• TensorFlow
• Langfuse
• LangGraph
• AI governance
• Model evaluation
• RAG pipelines
• Data preprocessing
• Feature engineering
• Spark
• Content moderation
• Hallucinations
• Langgraph
• Responsible AI
• Pipelines
• Generative Artificial Intelligence
• AI Safety
• Agentic Systems
• Workflow Management
• AI Research
• Data Preprocessing
• Ethical Standards And Conduct
• Administrative Functions
• Research
• Multi-Agent Systems
• Artificial Intelligence
• Application Development
• Applied Research
• Fundamental Science
• Benchmarking
• Communication
• Computer Science
• Data Processing
• Creativity
• E-Commerce Management
• Governance
• Leadership
• Scalability
• Innovation
• Problem Solving
• Python (Programming Language)
• Machine Learning Algorithms
• Machine Learning
• Mathematics
• Mentorship

• Technology
• Science & Research
• Software
• Data & Analytics
• Engineering
• Applied Researcher
• Generative Artificial Intelligence Engineer
• Software Developers
• Computer and Information Research Scientists

Minimum education

Master’s degree

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week