Lead initiatives in generative AI, identifying business scenarios where generative AI can be effectively applied

Research, design, and prototype cutting-edge generative AI approaches

Evaluate the feasibility of generative AI solutions for real-world use cases

Explore and analyze existing scientific research to inform solution development

Implement and validate generative AI solutions for diverse business challenges

Collaborate closely with the ML engineering team throughout all stages, from research to implementation

Work with product managers and business stakeholders to shape a clear vision of generative AI technology and its practical applications

Present results to stakeholders, effectively communicating both technical and business aspects of solutions

Minimum 3 years of relevant experience in Data Science, focusing on developing generative models such as LLMs, GANs, VAEs, and Diffusion models

Experience with computer vision and natural language processing, including working with multimodal data such as images, text, and audio

Familiarity with OpenAI GPT-x and experience in fine-tuning models

Proven ability to write production-ready code using best engineering practices

Strong programming skills in Python

Proficiency with at least one deep learning framework such as PyTorch or TensorFlow

Experience optimizing deep learning models for production

Hands-on experience with at least one cloud platform, such as AWS, Azure, or GCP

Excellent communication skills

Fluent English skills (written and spoken) at a B2+ level or higher

Experience with additional generative AI architectures and emerging techniques

Knowledge of reinforcement learning and self-supervised learning approaches

Familiarity with MLOps tools and practices for deploying and monitoring AI models