Machine Learning Engineer

Position: Staff Machine Learning Engineer
This job is with eBay, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

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 Role
At eBay, Risk & Compliance plays a critical role in protecting the integrity of our global marketplace and ensuring trust for millions of buyers and sellers worldwide. Our mission spans fraud prevention, regulatory compliance, financial crime, abuse detection, and policy enforcement-operating at massive scale and under constantly evolving regulatory requirements.
We are seeking a  Senior Staff Machine Learning Engineer  to serve as a  technical leader  within the Risk & Compliance organization. This role is responsible for  driving the architecture and delivery of end-to-end AI systems , with a strong emphasis on  Generative AI and agentic AI , to address complex, high-impact risk problems across the platform.
This is a senior technical role with  significant autonomy and influence , requiring deep hands-on expertise, strategic thinking, and the ability to lead initiatives that span multiple teams and domains.
Primary

Job Responsibilities     As a Senior Staff Machine Learning Engineer in Risk & Compliance, you will operate as a technical authority and multiplier. Your responsibilities include, but are not limited to:
Own and drive the technical vision  for large-scale ML and AI systems supporting fraud detection, risk assessment, compliance enforcement, and policy automation.

Architect and deliver  end-to-end AI solutions , from data strategy and feature engineering through model training, deployment, and real-time or batch inference.

Lead the design and implementation of  Generative AI and agentic AI systems , including LLM-based decision support, autonomous investigation agents, workflow orchestration, and human-in-the-loop systems.

Translate ambiguous regulatory, policy, and business requirements into  scalable, reliable, and explainable ML architectures .

Design and optimize  high-throughput ML and data pipelines  operating on massive, heterogeneous datasets across distributed systems.

Partner closely with applied researchers, policy teams, legal, operations, and platform engineering to ensure AI solutions are effective, compliant, and production-ready.

Act as a  technical owner across multiple initiatives , setting architectural standards, reviewing designs, and influencing long-term platform direction.

Drive  MLOps best practices  including model lifecycle management, automated testing, monitoring, retraining, and governance.

Ensure systems meet  risk, compliance, and responsible AI requirements , including robustness, auditability, fairness, and transparency.

Mentor senior engineers and ML practitioners, raising the technical bar and fostering a culture of engineering excellence.

Required Skills and Experience
Bachelor's, Master's, or PhD in Computer Science  or a related technical field, or equivalent practical experience.

8+ years of industry experience  building, deploying, and operating machine learning systems at scale.

Demonstrated success delivering  end-to-end ML and AI solutions  in production, including ownership of system architecture and long-term evolution.

Deep expertise in  Machine Learning, Deep Learning, and NLP , with hands-on experience in  Generative AI  (LLMs, RAG, prompt engineering, evaluation).

Experience designing or implementing  agentic AI systems , such as autonomous agents, tool-using agents, multi-step reasoning, or decision orchestration frameworks.

Strong background in  distributed systems and large-scale data processing  (e.g., Spark, Hadoop, streaming platforms).

Proficiency in  Python  and at least one additional language such as  Java or Scala .

Excellent system design skills, with a track record of building  scalable, reliable, and maintainable production systems .

Experience with  MLOps , including CI/CD for ML, model monitoring, performance tracking, and governance workflows.

Proven ability to  lead through influence , communicate complex ideas clearly, and collaborate effectively across engineering, product, and non-technical stakeholders.

Nice to Have       Experience applying ML or AI to  fraud detection, financial crime, abuse prevention, or regulatory compliance .

Hands-on experience deploying LLMs on …