Job Description

Key Responsibilities

Conduct deep learning research focused on video, audio, diffusion models,

transformers, and related generative or representation-learning approaches.


Explore cutting-edge methods in multimodal modeling, temporal modeling, and

high-fidelity generation.


Evaluate and synthesize recent research papers, identifying opportunities for novel

architectural improvements or new research directions.


Prototype new model architectures, algorithms, and training methodologies to validate

ideas.


Build proof-of-concept systems (POCs) to demonstrate feasibility and real-world

potential.


Develop experiments at scale, including data preparation, model training, benchmarking,

and ablation studies.


Collaborate with engineering teams to transition successful research into

production-ready components.


Stay current with advancements in deep learning, GPU acceleration, and emerging AI

techniques.

Required Qualifications

Strong understanding of deep learning theory and practical application, including

frameworks like PyTorch or JAX.


Experience with transformer architectures, diffusion models, or generative modeling paradigms.

Expertise in one or more of the following domains:

Video understanding, video generation, temporal models

Audio modeling, speech, or acoustic representation learning

Image or multimodal generative models

Proficiency in CUDA programming, GPU optimization, and performance engineering.

Ability to implement research ideas cleanly and efficiently in code.

Strong math foundation (probability, optimization, linear algebra).

Preferred Qualifications

Publications in top-tier AI/ML conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, Interspeech, etc.).

Experience training large-scale models with distributed compute.

Familiarity with model scaling laws, synthetic data generation, self-supervision, or curriculum learning.

Ability to reason about architectural trade-offs, data requirements, and computational efficiency.

Experience working with large video/audio datasets and modern preprocessing pipelines.

Experience:

Min 2 years