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Machine Learning Engineer at PayPal
San Jose, California, United States -
Full Time

Start Date

Immediate

Expiry Date

21 Feb, 26

Salary

270500.0

Posted On

23 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Spark, Tensorflow, Hadoop, Python, Pytorch, Machine Learning, Data Mining, Scala, SQL, C, C++

Industry

Software Development

Description
Job Duties: Design and build large-scale distributed systems to support the end-to-end machine learning (ML) lifecycle. Collaborate closely with data scientists, analysts, and other stakeholders to understand data requirements, deliver innovative solutions, and ensure the availability, reliability, and scalability of ML Platform. Facilitate seamless collaboration with cross-functional teams from Business and Technology domains to align project goals, gather requirements, and drive successful project outcomes. Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. Provide technical guidance, and foster a culture of collaboration, innovation, and continuous learning with team members. 1. Spark (2 years); 2. Tensorflow (2 years); 3. Hadoop (2 years); 4. Python (2 years); 5. Pytorch (2 years); 6. Machine Learning (2 years); 7. Data Mining (2 years); 8. Scala (2 years); 9. SQL (2 years); 10. C or C++ (2 years); EOE, including disability/vets. Salary: $190,819.00-270,500.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m. The total compensation for this position includes standard company benefits and is based on various factors including but not limited to relevant skills and experience. Your recruiter can share more information about our total compensation package during the hiring process. Must be legally authorized to work in the U.S. without sponsorship Subsidiary:
Responsibilities
Design and build large-scale distributed systems to support the end-to-end machine learning lifecycle. Collaborate closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver innovative solutions.