Conduct high-quality research in generative AI, including but not limited to designing algorithms for pre-training and post-training current autoregressive and diffusion models for multimodal data.
Design, implement, and validate new algorithms and models for augmented LLMs, pushing the boundaries of AI capabilities.
Developing and prototyping novel algorithms for fine-turning, retrieval augmented generation, and in-context learning for various generative models.
Developing algorithms for training and inference in Energy-Based Models.
Collaborate with cross-functional teams to apply research findings to develop new products or enhance existing ones.
Publish research papers in top-tier journals and conferences, sharing findings with the broader scientific community.
Stay abreast of the latest AI research and trends, identifying opportunities for innovation and improvement.
Mentor junior researchers and engineers, fostering a culture of knowledge sharing and collaboration.
Develop prototypes and proof-of-concept implementations to demonstrate the potential of research findings.
Engage with the academic community by attending conferences, workshops, and seminars.

Requirements

PhD in Computer Science, Artificial Intelligence, Machine Learning, Physics, Mathematics, or other related fields.
3+ years working experience with training and fine-tuning generative AI models including LLMs, diffusion models, or Energy-Based Models
Experience with test-time compute techniques, such as chain-of-thoughts, self–consistency, or reinforcement learning based verifiers, etc
Proven track record of research in generative models, demonstrated through first tier publications (e.g., NeurIPS, ICML, ICLR, or high impact journals), patents, or publicly available projects.
Proficiency in programming languages commonly used in AI research, such as Python, and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch).
Deep understanding of machine learning algorithms and principles, especially in the context of generative AI.
Strong mathematical background, with excellent skills in areas such as statistics, probability, linear algebra.
Creative and analytical thinking abilities, with a passion for solving complex problems.
Excellent communication skills, capable of conveying complex ideas clearly and engaging with both technical and non-technical audiences.

Benefits

Health & Wellbeing benefits
Personal & Professional Development programs
Unconditional Inclusion practices

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

generative AIalgorithm designpre-training algorithmspost-training algorithmsaugmented LLMsfine-tuningretrieval augmented generationEnergy-Based Modelsmachine learning algorithmsprogramming in Python

Soft Skills

creative thinkinganalytical thinkingcommunication skillsmentoringcollaboration

Certifications

PhD in Computer SciencePhD in Artificial IntelligencePhD in Machine LearningPhD in PhysicsPhD in Mathematics