Remote AI Lead

About the Role

Our client, a global leader in privacy-preserving AI solutions, is seeking an experienced Remote AI Lead specializing in Federated Learning. This is a fully remote position, allowing you to contribute your expertise from anywhere. You will lead the research, development, and implementation of federated learning strategies and platforms, enabling collaborative model training without centralizing sensitive data. This role is critical for advancing our capabilities in secure and privacy-conscious AI across various industries. The ideal candidate will have a strong background in machine learning, a deep understanding of federated learning principles, and proven leadership skills.

Key Responsibilities

• Lead the design and development of federated learning systems and algorithms.
• Oversee the end-to-end lifecycle of federated learning projects, from conception to deployment.
• Conduct research into novel federated learning techniques, including differential privacy, secure aggregation, and model personalization.
• Collaborate with cross-functional teams (data scientists, engineers, product managers) to integrate federated learning into client solutions.
• Establish best practices and guidelines for secure and efficient federated learning implementations.
• Evaluate and select appropriate frameworks and tools for federated learning (e.g., PySyft, TensorFlow Federated).
• Mentor and guide a team of AI researchers and engineers working on federated learning initiatives.
• Publish research findings and present work at leading AI conferences and workshops.
• Stay abreast of the rapidly evolving landscape of privacy-enhancing technologies and regulations.

Requirements

• Ph.D. or Master's degree in Computer Science, Machine Learning, Statistics, or a related quantitative field, with a focus on privacy-preserving AI or federated learning.
• 7+ years of experience in machine learning research and development, with at least 3 years dedicated to federated learning.
• Demonstrated expertise in developing and deploying federated learning algorithms.
• Strong understanding of differential privacy, homomorphic encryption, secure multi-party computation, and other privacy-enhancing technologies.
• Proficiency in Python and popular deep learning frameworks (TensorFlow, PyTorch).
• Experience with distributed systems and cloud computing platforms (AWS, Azure, GCP).
• Excellent leadership, communication, and collaboration skills, especially in a remote setting.
• Proven ability to drive research initiatives and deliver complex projects.
• Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, AISTATS) are highly desirable.

Benefits

Our client offers a highly competitive salary and performance bonus structure, reflecting the seniority and remote nature of this role. We provide comprehensive global health insurance, a robust retirement savings plan, and generous paid time off. As a remote-first organization, we prioritize flexibility and work-life balance. Employees benefit from a dedicated home office stipend, opportunities for continuous learning and professional development, and access to a vibrant online community of experts. You will have the autonomy to shape the future of privacy-preserving AI from your chosen location. Additional benefits include equity options and regular virtual team events.