Sr Manager, Machine Learning Engineering at PayPal

San Jose, California, United States -

Full Time

Start Date

Immediate

Expiry Date

27 Mar, 26

Salary

0.0

Posted On

27 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, ML Engineering, Model Optimization, Data Preprocessing, Cross-Functional Collaboration, Model Monitoring, Mentoring, ML Algorithms, Distributed Systems, Cloud Environments, MLOps Frameworks, Statistical Model Validation, Python, SQL, Personalization

Industry

Software Development

Description

Define and drive the strategic vision for machine learning initiatives within the team. Lead the development and optimization of 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. Mentor and guide junior engineers and data scientists. Ensure adherence to best practices and industry standards in ML development. 8+ years of experience in machine learning, data science, or ML engineering, with 4+ years leading technical teams. Strong track record delivering large-scale ML systems, especially in personalization, ranking, recommendations, or NBA decisioning. Deep understanding of ML algorithms (LTR, embeddings, collaborative filtering, uplift modeling, RL concepts) and real-time inference architectures. Hands-on experience with distributed systems (Kafka, Flink, Spark), cloud environments, and modern MLOps frameworks. Experience managing teams spanning multiple competencies (ML Engineering, DS, MLOps). Strong foundation in experimentation, causal inference, and statistical model validation. Expertise with Python, SQL, and standard ML/statistical tooling. 8+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Experience leading others Experience with large-scale personalization platforms or recommendation systems in consumer-facing apps. Background working with GCP, Vertex AI, or other cloud ML platforms. Familiarity with monitoring tools (e.g., Datadog) and model observability frameworks. Experience with LLM-based personalization, vector search, or reinforcement learning for decisioning. Published research in ML, RecSys, IR, or related areas.

Responsibilities

Define and drive the strategic vision for machine learning initiatives. Lead the development and optimization of machine learning models while overseeing the preprocessing and analysis of large datasets.