Responsibilities
- Develop and implement generative AI models, including LLMs, text-to-image and generative AI models.
- Train and evaluate models using large datasets.
- Troubleshoot and debug code to ensure high-quality results.
- Keep up to date with the latest developments in the field of generative AI and apply relevant new knowledge to the company's AI projects.
- Deep understanding of how to scale models and their limitations. Ability to quickly identify opportunities for model improvement
- Use predictive modeling to enhance and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
- Collaborate with different teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Lead all data experiments under the iterative testing framework.
- Engage with stakeholders to understand business challenges and develop data-driven solutions.
- Conduct advanced data analysis and design highly complex algorithmic models.
- Communicate complex quantitative analysis in a clear, precise, and actionable manner.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 2+ years of experience in developing and training AI/ML models.
- Experience with data querying languages like SQL, scripting languages like Python, and/or statistical/mathematical software e.g. R
- Knowledge of state-of-the-art generative AI models such as GPT-3, DALL-E, and CLIP.
- Experience with Cloud infrastructure and Platforms - Azure /Google Cloud Platform/AWS
- Working experience with Kore.AI and Prompt Engineering is a big plus
- Experience with training and evaluating large-scale models on high-performance computing clusters.
- Strong understanding of deep learning, natural language processing, and computer vision.
- Excellent problem-solving skills and ability to work independently and in a team environment.
Preferred Qualifications:
- Bachelor's or master's degree in computer science, Data Science, Statistics, Math, Physics, or other Science related discipline with course work in AI/ML.
- Demonstrated experience in developing and training AI models
- Strong knowledge of deep learning, natural language processing, and computer vision.
- Experience with scaling up generative models and deploying them in production environments.
- Ability to work collaboratively in a team environment and communicate complex technical concepts to non-technical stakeholders.