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.

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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.

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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.

Associate Architect - AI/ML