Applied Researcher 1

eBay • Portland, OR

2d • Hybrid

About The Position

eBay, Inc. seeks Applied Researcher I in Portland, OR. This role involves leading the design and implementation of sophisticated algorithms to enhance the selling experience and build user trust. The position requires developing machine learning models and scalable data pipelines to deliver practical, data-driven solutions. The researcher will stay informed about the latest advancements in algorithms and machine learning, integrating innovative techniques to improve business metrics and user experience. Collaboration with cross-functional teams to transition research insights into production systems, ensuring scalability and performance, is also a key aspect. Conducting experiments and analyzing data to drive continuous model improvements, and effectively communicating research findings and technical concepts to both technical and non-technical stakeholders are expected. Expertise in machine learning and data science, with experience in areas such as Generative AI, NLP, recommendation systems, ranking, fraud detection, or online advertising is required. Proficiency in Python, Java, or similar languages, with experience using ML frameworks like TensorFlow or PyTorch, and familiarity with big data tools such as Hadoop, Spark, and SQL are necessary. Partial telecommuting is permitted from within a commutable distance.

Requirements

• Master’s degree, or foreign equivalent, in Computer Science, Engineering (any field), or a closely related field plus two years of experience in the job offered or a related occupation.
• OR Bachelor’s degree, or foreign equivalent, in Computer Science, Engineering (any field) or a closely related field plus five years of experience in the job offered or a related occupation.
• Experience on working with high-impact LLM applications (2 years)
• Designing scalable labeling strategies (human-in-the-loop, weak supervision, and synthetic data generation) with a focus on quality control and bias mitigation (2 years)
• Evaluating and fine-tuning vision based foundation models for diverse tasks such as classification, segmentation and detection (2 years)
• Developing and optimizing machine learning and deep learning models using PyTorch (2 years)
• Experience with working on data pipelines and ETL workflows using SQL and Python (2 years)
• Conducting AI research and development involving models such as Convolutional Neural Networks (CNNs) and Transformers (2 years)
• Experience with working with large-scale datasets for data processing and model training (2 years)
• Applying object-oriented design principles and developing scalable software systems in Python (2 years)
• Building and evaluating end-to-end AI systems, from data ingestion to model deployment (2 years)
• Using version control systems (Git) and cloud platforms (AWS, GCP) for machine learning development and deployment (2 years)
• Implementing containerization using Docker to run isolated services (2 years)
• Using CI/CD pipelines with GitHub for software integration and deployment workflows (2 years)
• Applying automated labeling techniques to accelerate data generation and model iteration (2 years)
• Optimizing models for runtime efficiency, including improvements in latency and memory consumption performance (2 years)

Nice To Haves

• Expertise in machine learning and data science, with experience in areas such as Generative AI, NLP, recommendation systems, ranking, fraud detection, or online advertising.
• Proficiency in Python, Java, or similar languages, with experience using ML frameworks like TensorFlow or PyTorch.
• Utilize familiarity with big data tools such as Hadoop, Spark, and SQL.

Responsibilities

• Lead the design and implementation of sophisticated algorithms to enhance the selling experience and build user trust.
• Develop machine learning models and scalable data pipelines to deliver practical, data-driven solutions.
• Stay informed about the latest advancements in algorithms and machine learning, integrating innovative techniques to improve business metrics and user experience.
• Collaborate with cross-functional teams to transition research insights into production systems, ensuring scalability and performance.
• Conduct experiments and analyze data to drive continuous model improvements.
• Communicate research findings and technical concepts effectively to both technical and non-technical stakeholders.

Benefits

• 401(k) eligibility
• various paid time off benefits, such as PTO and parental leave
• medical benefits
• financial benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level