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Ebay MTS2- ML Staff Software Engineer - Risk 
India, Karnataka, Bengaluru 
321911

15.07.2025

What you will accomplish :

  • Design, deliver, and optimize high-performance, large-scale applications, data pipelines, and ML service infrastructure with exceptional speed and reliability.

  • Enhance core products by skillfully integrating, fine-tuning, and deploying advanced machine learning models for optimal performance and impact.

  • Command the full software development lifecycle—from initial design and architecture to coding, testing, deployment, and maintenance—while producing clean, efficient, and documented code.

  • Develop and execute sound technical strategies for complex projects, taking into account business goals, timelines, and long-term impact.

  • Work closely with product managers and partners to translate business requirements into robust technical solutions, ensuring alignment across teams.

  • Take ownership of cross-team engineering efforts and guide junior team members, setting a high standard for technical excellence and professional growth.

  • Drive innovation by developing novel solutions to challenging problems and actively contribute to a culture of knowledge sharing by both teaching and learning from others.

What you will bring :

  • Masters in Computer Science or a related field with 7+ years of experience (or BS/BA with 8+ years) in building large-scale distributed applications and backend services.

  • A solid foundation in Data Structures, Algorithms, Object-Oriented Programming, Software Design/architecture, and core Statistics knowledge

  • Experience in the close examination of data, computation of statistics, and deriving of data insights

  • Proven experience designing and operating Big Data processing pipelines (Hadoop, Spark) and working with NoSQL databases or key-value stores (e.g., MongoDB, Redis).

  • Hands-on experience with the end-to-end lifecycle of machine learning, including model deployment and application at scale. Experience in AI research or industrial recommendation systems is a significant plus.

  • Experience with cloud services and familiarity with Large Language Models (LLMs) or prompt engineering is highly desirable.

  • A passion for technical excellence, excellent communication skills, and a "can-do" attitude with a willingness to learn and master new technologies.