AI/ML Staff Software Engineer

ebayinc

Bengaluru 5 Years Exp Posted 212d ago

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.

Education: Bachelor’s or Master’s in CS, Engineering, Math, or related field; PhD preferred but not required.