Key Responsibilities :
- Explore advanced topics in Kernel Methods, Federated Learning, Secure & Private AI, Optimization, and Privacy-Preserving Machine Learning.
- Build proof-of-concept implementations to validate and demonstrate theoretical advancements.
Lead & Mentor : Guide junior researchers, foster innovation, and maintain high research standards within the team.
Work closely with cross-functional teams, universities, and international research communities.Contribute to high-impact publications and represent the lab at top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, JMLR). uTranslate research outcomes into scalable AI solutions that address real-world challenges in security, distributed systems, and model adaptability.Required Qualifications :
Ph.D. in Computer Science, Mathematics, Statistics, Electrical Engineering, or a related quantitative field. 47 years of hands-on experience in AI / ML research and development.Strong theoretical foundation in one or more of the following areas : Functional Analysis Probability and Statistics Optimization Theory Machine Learning Theory Demonstrated research excellence with publications in top-tier conferences / journals (NeurIPS, ICML, ICLR, AAAI, JMLR, etc.).Proficiency in Python and popular ML frameworks (PyTorch, TensorFlow, or JAX).Preferred Skills & Experience :
Expertise in Federated Learning, Secure Multi-Party Computation (SMPC), or Differential Privacy (DP). Familiarity with distributed systems and scalable ML architectures.Strong algorithm design and implementation skills.Experience with academic-industry research collaborations.Excellent communication skills and a passion for mentoring emerging researchers.Opportunity to define next-generation AI research directions.Collaborate with a diverse, global network of AI scientists.Work on projects with real-world impact and academic visibility.Support for conference travel, paper publication, and continued research funding.AI ResearchMachine Learning TheoryFederated LearningSecure AIKernel MethodsOptimizationDifferential PrivacySMPCPrivacy-Preserving MLDistributed LearningPythonPyTorchTensorFlowResearch PublicationAlgorithm Design(ref : hirist.tech)