Responsibilities
- 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
Basic qualifications
- 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
Preferred qualifications
- 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
Tags & focus areas
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