Ebay AI/ML Staff Software Engineer 

India, Karnataka, Bengaluru 

845076757

• Design and build machine learning models to detect fraud, bot attacks, collusion etc.

• Perform feature engineering, model development, evaluation, and optimization for high-accuracy ML applications.

• Fine-tune and implement Deep Neural Network (DNN) architectures.

• Construct robust ML pipelines for training, validation, and deployment using modern ML stacks.

• Apply prompt engineering techniques with Generative AI models (LLMs, diffusion models, etc.) to tackle application-driven problems.

• Leverage vector databases and build/optimize embeddings for search, retrieval, and semantic understanding.

• Lead efforts in simulation, synthetic data generation, and experimentation.

• Build reliable APIs and services that expose ML model outputs for real-time decisioning.

• Evaluate bias and fairness across population subgroups.

• Maintain logging, tracing, and alerting for model inputs/outputs, feature importance, versions, and pipeline steps.

• Lead and participate in data validation, preprocessing, and cleansing workflows to ensure ML readiness.

• Work closely with engineers, product managers, and collaborators to develop scalable ML-powered applications.
  

What will you bring?

• At least 5 years of experience in building AI/ML-based products and solutions in production environments.

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

• Proven expertise in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras.

• 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.

• Experience in the close examination of data and computation of statistics

• Proficiency in working with large scale data in hadoop and spark.

• Proficient with prediction accuracy, latency, throughput, confidence scores, and drift (data & concept).

• Strong programming, system design, and debugging skills.

• Experience working in domains such as fraud detection, credit risk, compliance, advertising, or recommendations is highly preferred.

• Publication of research papers or technical articles in ML conferences or journals is highly desirable.