Staff Machine Learning Engineer

PayPal
San Jose
Workplace: OnsiteFull timeUSD 193,978 - 333,500 annuallyFunction: Data Science & Machine LearningExperience: 4-6 yearsEducation: mastersSkills: ["Communication"]

Develop and deploy advanced ML and generative AI systems to personalize PayPal product experiences and improve recommendations across customer lifecycles. Build scalable, low-latency ranking models and near real-time feature engineering pipelines using stream and batch processing. Fine-tune LLMs and apply reinforcement learning approaches, partnering with engineering and Platforms teams while communicating model results to technical and non-technical stakeholders. Telecommuting permitted within commuting distance.

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FursaFursa
PayPal
PayPal
2 days ago

Staff Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live
Reposted: similar role first listed 6 months ago

Job Summary

Develop and deploy advanced ML and generative AI systems to personalize PayPal product experiences and improve recommendations across customer lifecycles. Build scalable, low-latency ranking models and near real-time feature engineering pipelines using stream and batch processing. Fine-tune LLMs and apply reinforcement learning approaches, partnering with engineering and Platforms teams while communicating model results to technical and non-technical stakeholders. Telecommuting permitted within commuting distance.
Location: San Jose
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop and implement advanced ML models to solve business problems for product recommendations and customer lifecycle optimization.
  • •Design and deploy scalable generative AI solutions within PayPal’s ecosystem.
  • •Build and deploy scalable ML/AI solutions to improve seamless customer experiences in collaboration with engineering and Platforms.
  • •Train, test, and productionize ranking/recommendation models for real-time systems with strict latency constraints.
  • •Communicate model and analysis results to technical and non-technical audiences and influence partners and customers with insights.

Pay and Benefits

Salary: USD 193,978 - 333,500 annually
Equity and Bonus:Equity
Perks:Health InsuranceRetirement

Key Requirements

  • •Master’s degree (or foreign equivalent) in Computer Science, Engineering, Physical Systems, or a related field plus 4 years of experience in the role or a related occupation.
  • •Employer accepts a Bachelor’s degree (or foreign equivalent) plus 6 years of experience in the role or a related occupation.
  • •Experience with machine learning models, including reinforcement learning with contextual multiarmed bandits and Neural Bandit.
  • •Experience fine-tuning LLMs such as Llama and RoBERTa using PyTorch or TensorFlow, including LoRA.
  • •Experience with PyTorch, TensorFlow, Scala, Java, and Python to build and productionize real-time recommendation/ranking and low-latency systems.
Experience:4-6 yearsMachine learningGenerative AIRecommendation systems
Education:Master's
Skills:Communication
Tech Stack:Machine learningGradient boosted decision treeGraph neural networksDeep learningGenerative AIReinforcement learningContextual multiarmed banditsNeural BanditLlamaRoBERTaPyTorchTensorflowLoRAScalaJavaPythonApache FlinkApache KafkaApache SparkTwo-Tower

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

PayPal
Global online payments platform enabling digital and mobile payments, money transfers, and merchant services for consumers and businesses, supporting e‑commerce transactions across multiple currencies and payment methods.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 1998
WebsiteLinkedIn