Senior ML Engineer
2 weeks ago
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
As an ML Engineer at eBay's Risk team, you'll be part of an exciting journey that is instrumental in maintaining eBay to be a safe and trusted marketplace. The role involves working on critical projects related to the Risk product, which enhances the model lifecycle management for applied researchers, data scientist and ML engineers like yourself. This team is known for fostering an innovative culture and a collaborative environment, encouraging continuous learning and growth. The Risk Engineering team is a key player in keeping the marketplace safe for all buyers and seller.
What You Will Accomplish
- Drive innovations in building models using ML/NLP/AI to prevent fraud and increase trust at eBay marketplace.
- Collaborate across multifunctional teams to integrate cutting-edge ML solutions that directly impact eBay's Risk mitigation and fraud prevention.
- Implement and refine model deployment processes that facilitate quick and efficient model releases from offline to online environments.
- Contribute to multi-functional problem-solving activities, assisting in developing advanced technological solutions for complex business situations.
- Engage in continuous learning opportunities, staying updated with the latest industry trends and technologies to drive eBay's success further.
What You Will Bring
- At least 5 years of experience in building, training and productionalizing AI model or conventional models.
- Strong Expertise with Python, Keras, Tensor Flow, Pytorch, Scikit modules is a must have.
- Deep understanding of machine learning fundamentals, algorithms, and model evaluation techniques.
- Hands-on experience with ML Ops tools and best practices.
- Experience with OCR, NLP, vector search, embeddings, and LLM-based applications is strong desired.
- Experience in the close examination of data and computation of statistics.
- Expertise in building features in feature store.
- Proven skills in enhancing model lifecycle management, particularly within complex ML platforms.
- Ability to work effectively in a collaborative and agile environment, managing multiple projects simultaneously.
- Deep understanding of both CPU and GPU serving platforms, and effectively bridging technological gaps.
- Experience working in large-scale AI transformations within prominent product companies in a plus.
- Strong communication skills and the ability to articulate complex technical concepts to diverse audiences.
- Experience in adversarial space like risk, security, bot mitigation or ads, recommendation are a strong plus.
- Experience with prompt engineering + RAG with COT, COV to build production grade solution will be strongly desired.
Educational Qualification
Bachelor's or Master's in CS, Engineering, Math, or related field; PhD preferred but not required.
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