01Overview
Roles and Responsibilities
Design, develop, and deploy advanced AI models with a focus on generative AI, including transformer architectures (e.g., GPT, BERT, T5) and other deep learning models used for text, image, or multimodal generation.
Work with extensive and complex datasets, performing tasks such as cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training.
Collaborate with cross-functional teams (e.g., product, engineering, data science) to identify project objectives and create solutions using generative AI tailored to business needs.
Implement, fine-tune, and scale generative AI models in production environments, ensuring robust model performance and efficient resource utilization.
Develop pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production.
Stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability.
Document and communicate technical specifications, algorithms, and project outcomes to technical and non-technical stakeholders, with an emphasis on explainability and responsible AI practices.
Qualifications Required
Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field. Relevant Ph.D. or research experience in generative AI is a plus.
Experience: 12 - 16 Years of experience in machine learning, with 8+ years in designing and implementing generative AI models or working specifically with transformer-based models.
Skills and Experience Required
Generative AI: Transformer Models, GANs, VAEs, Text Generation, Image Generation
Machine Learning: Algorithms, Deep Learning, Neural Networks
Langchain, GPT-4, Sagemaker/Bedrock
Programming: Python, SQL; familiarity with libraries such as Hugging Face Transformers, PyTorch, TensorFlow
MLOps: Docker, Kubernetes, MLflow, Cloud Platforms (AWS, GCP, Azure)
Data Engineering: Data Preprocessing, Feature Engineering, Data Cleaning
Why you'll love working with us:
Opportunity to work on technical challenges with global impact.
Vast opportunities for self-development, including online university access and sponsored certifications.
Sponsored Tech Talks & Hackathons to foster innovation and learning.
Generous benefits package including health insurance, retirement benefits, flexible work hours, and more.
Supportive work environment with forums to explore passions beyond work.
This role presents an exciting opportunity for a motivated individual to contribute to the development of cutting-edge solutions while advancing their career in a dynamic and collaborative environment. .
