01Overview
How You Will Make an Impact:
AI Research Development
Design, develop, and fine-tune state-of-the-art generative AI models (e.g., GPT, Stable Diffusion, DALL E, BERT, LLaMA, T5, etc.).Optimize LLMs, multimodal AI, and other generative models for performance, efficiency, and scalability.Stay up to date with the latest advancements in the Generative AI domain.Implement techniques such as transfer learning, model compression, reinforcement learning (RLHF), and adversarial training.Technical Leadership Team ManagementLead and mentor a team of AI engineers.Define and enforce best practices for AI model development, MLOps, and deployment.Collaborate with cross-functional teams, including product, design, data engineering, and software engineering.Drive AI project roadmaps and ensure timely execution while balancing research and productization.AI System Architecture InfrastructureDesign and implement scalable, high-performance AI architectures for real-world applications.Work with cloud-based AI services (AWS, GCP, Azure) and on-premise solutions to deploy AI models.Ensure AI models are optimized for low latency, cost efficiency, and high throughput.Data Engineering Model TrainingOversee data collection, augmentation, and preprocessing pipelines for training generative AI models.Implement self-supervised learning, synthetic data generation, and data labeling strategies.Ensure AI models comply with data privacy regulations (GDPR, CCPA, etc.).Performance Monitoring OptimizationImplement real-time monitoring, logging, and debugging for AI models in production.Conduct A/B testing and user feedback loops to enhance AI performance.What You Bring to the Team:
7+ years of experience in AI/ML engineering, including research, model development, and deployment.Strong background in deep learning frameworks such as TensorFlow, PyTorch, or JAX.Expertise in optimizing large-scale machine learning models for efficiency and performance.Experience in leading AI teams and managing end-to-end AI lifecycle development.Familiarity with cloud-based AI solutions (AWS, GCP, Azure) and MLOps best practices.Strong understanding of data privacy laws and ethical AI considerations.Minimum Bachelors Degree in Computer Science, AI, Machine Learning, or a related field. Master s/Ph.D. preferred. .
