MTS 1, Machine Learning Engineer

PayPal-posted 27 days ago

Full-time • Entry Level

Hybrid • San Jose, CA

5,001-10,000 employees

Credit Intermediation and Related Activities

Resume

Match Score

Upload and Match ResumeTrack Jobs with Teal

PayPal, Inc. seeks MTS 1, Machine Learning Engineer in San Jose, CA Job Duties: Create innovative artificial intelligence (AI)/machine learning (ML) solutions that enhance personalization for PayPal users, with a focus on Al/ML algorithms supporting ranking and recommendation problems among other challenges. Write scalable, production-quality code to deploy models on company infrastructure, optimizing for performance and efficiency. Collaborate with cross-functional teams, including engineering, product, and marketing, to design, develop, and track key performance indicators for ranking and recommendation models. Conduct experiments to measure these key performance indicators as well as derive actionable insights from the data, to continually improve the technology and drive business outcomes. Write scalable production-quality code in Python, Java, Scala, or a similar programming language. Design and implement data engineering pipelines using technologies like Hive, SQL, BigQuery, or Spark. Utilize experience with Graph-based algorithms and infrastructure, experience working on feed-based ML ranking and recommendation systems, and prior experience working in a cloud-based environment such as GCP (Google Cloud Platform). Utilize hands-on experience with conducting experiments in various areas of personalization and causal inferencing. Partial telecommuting permitted from within a commutable distance.

Create innovative artificial intelligence (AI)/machine learning (ML) solutions that enhance personalization for PayPal users, with a focus on Al/ML algorithms supporting ranking and recommendation problems among other challenges.
Write scalable, production-quality code to deploy models on company infrastructure, optimizing for performance and efficiency.
Collaborate with cross-functional teams, including engineering, product, and marketing, to design, develop, and track key performance indicators for ranking and recommendation models.
Conduct experiments to measure these key performance indicators as well as derive actionable insights from the data, to continually improve the technology and drive business outcomes.
Write scalable production-quality code in Python, Java, Scala, or a similar programming language.
Design and implement data engineering pipelines using technologies like Hive, SQL, BigQuery, or Spark.
Utilize experience with Graph-based algorithms and infrastructure, experience working on feed-based ML ranking and recommendation systems, and prior experience working in a cloud-based environment such as GCP (Google Cloud Platform).
Utilize hands-on experience with conducting experiments in various areas of personalization and causal inferencing.

Master's degree, or foreign equivalent, in Computer Science, Engineering, or a closely related field plus two years of experience in the job offered or a related occupation.
Experience designing, training, and deploying scalable machine learning models to solve business problems, leveraging statistical algorithms and advanced machine learning concepts (1.5 years).
Experience developing AI solutions, utilizing deep learning, reinforcement learning models, and large language models (LLMs) to enhance automation, optimization, and intelligent decision-making across various domains (1.5 years).
Experience designing and implementing personalized recommendation algorithms using collaborative filtering, hybrid approaches, or deep learning models to enhance user experience and engagement (1.5 years).
Experience conducting exploratory data analysis (EDA), statistical modeling, and visualization to derive insights, identify patterns, and make data-driven decisions (1.5 years).
Experience in writing scalable, efficient, and production-ready Python code for machine learning, data processing, and automation, utilizing industry-standard libraries and frameworks (1.5 years).
Experience writing complex SQL queries using SQL Query, optimizing database performance, and managing large-scale data storage solutions for analytics and application development (1.5 years).
Experience designing and deploying scalable, secure, and high-performance cloud-based applications using platforms such as AWS, GCP, and Azure for ML model deployment and data processing (1.5 years).
Experience designing, executing, and analyzing A/B tests to measure the impact of changes, optimize product performance, and improve key business metrics using statistical methodologies (1 year).

flexible work environment
employee shares options
health and life insurance

Track Jobs with Teal

Job Search Resources

•

AI Resume Builder

•

Machine Learning Engineer Resume Examples

•

Machine Learning Engineer Cover Letter Examples

MTS 1, Machine Learning Engineer

Job Search Resources

Tools

Career Hubs

Guides

Company