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

Start Date

Immediate

Expiry Date

14 Jan, 26

Salary

0.0

Posted On

16 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Model Optimization, Data Analysis, Model Deployment, Cross-Functional Collaboration, Performance Monitoring, Mentoring, ML Frameworks, Cloud Platforms, MLOps, Distributed Systems, LLMs, Multi-Agent Systems, Open-Source Contributions, Research Publications, Patents

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. Minimum of 12 years of relevant work experience and a Bachelor's degree or equivalent experience. Deep expertise with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Extensive experience with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Proven track record of leading the design, implementation, and deployment of machine learning models. Advanced degree (Ph.D./Master's) in Computer Science, AI, Machine Learning, or related field. Hands-on experience with LLMs, multi-agent systems, or autonomous agents. Contributions to open-source projects, research publications, or patents in AI. Strong background in distributed systems, MLOps, and experimentation platforms. Experience working in AI research teams or innovation-focused environments.
Responsibilities
Define and drive the strategic vision for machine learning initiatives within the team. Lead the development and optimization of machine learning models and oversee the preprocessing and analysis of large datasets.