Staff Software Engineer - Machine Learning Job at Relha LLC in San Jose

Staff Software Engineer – Machine Learning
Job Summary:
Join PayPal’s Consumer Product Catalog and Consumer Search team and help build the next generation of product discovery for millions of global shoppers. We own the backend and data infrastructure that powers search, recommendations, and catalog knowledge at global scale.

As a Machine Learning Engineer, you’ll contribute to key components of the product search stack - including indexing pipelines, and query-time services that deliver fast and relevant search results. You’ll collaborate closely with backend engineers and catalog data teams to enable intelligent, contextual, and scalable search capabilities.

We’re looking for motivated and collaborative engineers who thrive on solving complex problems in large‑scale search systems. You will work on challenges such as query and document understanding, product entity modeling and enrichment, taxonomy structuring, retrieval and ranking algorithms, and search quality evaluation. You will build models that enhance search relevance and ranking, delivering highly relevant results to users across the PayPal ecosystem. The ideal candidate brings strong experience in machine learning systems, takes ownership of the project from research and prototyping to production deployment, and is eager to shape modern, AI‑powered search experiences.

Responsibilities:

Lead the development and optimization of advanced machine learning models.

Oversee the preprocessing and analysis of large datasets.

Deploy and maintain ML solutions in production environments.

Collaborate with cross‑functional teams to integrate ML models into products and services.

Monitor and evaluate the performance of deployed models, making necessary adjustments.

Expected Qualifications:

5+ years relevant experience and a Bachelor’s degree OR any equivalent combination of education and experience.

Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit‑learn.

Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Additional Responsibilities & Preferred Qualifications:

8+ years of industry experience with deep learning architectures, building, fine‑tuning and deploying ML models in production.

Strong proficiency in Python, Scala, or other programming languages.

Experience working with large datasets, data processing pipelines (e.g., Dataflow, Spark, Flink), and scalable architectures.

Strong communication and collaboration skills, with the ability to work effectively across teams and contribute to a high‑performing engineering culture.

Experience working on search or recommendation systems at scale.

Familiarity with A/B testing and experimentation methodologies for search relevance improvement.

The pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay, including base pay and commission‑based compensation, for this role by location is:
For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in‑person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Primary Location | Pay Range:
For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in‑person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Commitment to Diversity and Inclusion
PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

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In Summary: The ideal candidate brings strong experience in machine learning systems, takes ownership of the project from research and prototyping to production deployment . The pay for this role will depend on where you work and the relevant experience and expertise you bring . For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in‑person collaboration and 2 days at your choice of either the PayPal office or your home workspace .

En Español:

Ingeniero de software Machine Learning Job Sumario: Únete al equipo de búsqueda y catálogo de productos de consumo de PayPal para ayudar a construir la próxima generación del descubrimiento de productos para millones de compradores globales. Somos propietarios de la infraestructura de backend y datos que impulsa las búsquedas, recomendaciones y conocimientos de catálogos a escala global. Como ingeniero de aprendizaje automático, contribuirás con componentes clave de la pila de búsqueas de productos - incluyendo tuberías de indexación y servicios en tiempo de consulta que proporcionan resultados de búsquieda rápidos y relevantes. Colaborarás estrechamente con los ingenieros de fondo e equipos de datos de catálicos para habilitar, capacitar contextuales y escalables buscas inteligentes. Buscamos ingenieros motivados y colaborativos que prosperen en resolver problemas complejos en sistemas de busca a gran escala. Trabajarás en desafíos como la comprobación y el entendimiento de documentos, la modelado de entidades y la clasificación de resultados, mejorar la calidad de los productos, evaluar algoritmos de recuperación y evaluación, así como crear modelos de relevancia y clasificación de los usuarios dentro del ecosistema de Google. El candidato ideal aporta una fuerte experiencia en sistemas de aprendizaje automático, toma la propiedad del proyecto desde la investigación y el prototipado hasta la implementación de producción, y está ansioso por dar forma a experiencias modernas de búsqueda basadas en IA. Responsabilidades: Dirigir el desarrollo y optimización de modelos avanzados de machine learning. Supervisar el preprocesamiento y análisis de grandes conjuntos de datos. Implementar y mantener soluciones ML en entornos productivos. Colaborar con equipos interfuncionales para integrar los modelos ML en productos y servicios. Monitorear y evaluar el rendimiento de los modelos implementados, haciendo los ajustes necesarios. Qualificaciones esperadas: 5+ años de experiencia relevante y un título de licenciatura o cualquier combinación equivalente de educación y experiencia. Experiencia extensa con marcos como MLORFlow, Tensorch o scikitlearn. La experiencia en las plataformas de búsqueo (AWS, GCP) e ingeniería de piezas de datos y otros tipos de trabajo (Py-levels), que contribuirá a mejorar sus habilidades profesionales en arquitectura de diseño a gran escala. El rango de remuneración esperado, incluido el salario básico y la compensación basada en comisiones, para este rol por ubicación es: Para la mayoría de los empleados, el modelo de trabajo híbrido equilibrado de PayPal ofrece 3 días en la oficina para una colaboración efectiva en persona y 2 días al elegir ya sea la oficina de PayPal o su espacio de trabajo doméstico, asegurando que tenga las mismas ventajas y conveniencias de ambos lugares.