Job VC

Key Responsibilities
Design, develop, and optimize deep learning models using PyTorch.
Build and maintain scalable training and evaluation pipelines.
Lead model selection, experimentation, and fine-tuning activities.
Improve training performance, efficiency, and scalability across large datasets and compute environments.
Work with multimodal data sources, including video, images, and audio.
Provide technical guidance on AI architecture, training strategies, and best practices.
Collaborate closely with product, engineering, and research teams to translate business objectives into AI solutions.
Support deployment and operationalization of machine learning models in production environments.
Required Experience
5+ years of experience in Machine Learning, Data Science, or AI Engineering roles.
Strong hands-on experience developing deep learning models with PyTorch.
Proven experience building and optimizing training pipelines for machine learning systems.
Deep understanding of model training, hyperparameter tuning, and performance optimization.
Experience working with computer vision, audio processing, or multimodal AI applications.
Strong software engineering skills and experience developing production-ready ML solutions.
Experience with cloud-based or distributed training environments.
Preferred Qualifications
Experience applying machine learning techniques within behavioral science, human behavior analysis, affective computing, or related domains.
Experience with video understanding, speech/audio analysis, or multimodal foundation models.
Familiarity with MLOps practices, model monitoring, and scalable deployment architectures.
Experience working with large-scale datasets and distributed training frameworks.