Staff ML Software Engineer

At eBay were more than a global ecommerce leader were changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. Were 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. Were 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 & Role:

The Compliance Engineering team at eBay is passionate about prohibited restricted and counterfeit compliance detection and is dedicated to ensuring that eBays marketplace adheres to all relevant regulations and internal policies.

The team develops and maintains sophisticated AI-driven tools and scalable backend systems that automatically identify and assess items listed on the platform. By applying sophisticated data models machine learning algorithms and rules-based engines they detect products that may be illegal harmful non-compliant with trade regulations or counterfeit.

As a Staff ML Engineer you will help lead the technical direction of a next-generation AI and ML platform while enabling GenAI and LLM-powered applications at enterprise scale.

You will architect systems that power compliance intelligence while also influencing the broader AI platform strategy across eBay. The role is ideal for someone who thrives at the intersection of system architecture ML infrastructure and powerful AI innovation.

What You Will Accomplish

• Architect & Scale: Design and build robust scalable systems and low-latency APIs that support high-throughput machine learning applications including LLM inference and GenAI pipelines.

• Platform Ownership: Lead the development of a modern AI platform supporting data prep model training serving monitoring and observabilitybuilt for modular reuse and horizontal scale.

• GenAI Enablement: Architect and deploy GenAI systems including retrieval-augmented generation (RAG) vector search timely engineering frameworks and GPU inference optimization.

• Tooling & Infrastructure: Drive adoption of groundbreaking ML infrastructureintegrating orchestration tools (Kubeflow Airflow) MLOps workflows (MLflow) and scalable serving layers (Triton TensorRT vLLM).

• Multi-functional Influence: Align platform capabilities with product ML science and compliance engineering teams to deliver unified solutions across domains.

• Technical Leadership: Own architectural vision perform meticulous code reviews and lead technical deep-dives and spike efforts into emerging tech.

• Culture & Mentorship: Mentor engineers across teams champion engineering excellence and build a forward-leaning culture of experimentation and delivery velocity.

What You Will Bring

• Prefer PhD or MS in Computer Science Electrical Engineering or related field with 8 years of experience in software engineering with a focus on large-scale high-performance distributed systems.

• Proven experience designing and scaling AI/ML platforms and servicesespecially those optimized for large model training and GenAI inference.

• Strong programming skills in Python Java or C with experience in frameworks like TensorFlow PyTorch.

• Deep understanding of database systems: SQL NoSQL vector databases graph databases. Strong foundation in building data architectures for ML applications.

• Experience building and deploying GenAI/LLM systems including RAG pipelines custom embeddings vector indexing and GPU-accelerated inference.

• Familiarity with tools and frameworks including Docker Kubernetes Spark Hadoop Kafka MLflow Airflow Kubeflow Nvidia Triton Nvidia TensorRT vLLM .

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The base pay range for this position is expected in the range below:

Base pay offered may vary depending on multiple individualized factors including location skills and experience. The total compensation package for this position may also include other elements including a target bonus and restricted stock units (as applicable) in addition to a full range of medical financial and/or other benefits (including 401(k) eligibility and various paid time off benefits such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

If hired employees will be in an at-will position and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time including for reasons related to individual performance Company or individual department/team performance and market factors.

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