We are looking for a dedicated Data Engineer with a focus on Generative AI (GenAI) to join our team. The prospective candidate should be adept in handling large datasets, implementing and scaling generative AI models, including but not limited to language models and text-to-image applications. Familiarity with Python and machine learning frameworks is essential, along with a deep understanding of cloud platforms like Azure.
Responsibilities
- Design and build scalable data pipelines to support generative AI model development, using technologies such as Azure, GCP, or AWS.
- Collaborate with data scientists to develop and implement GenAI models, including LLMs, text-to-image, and other generative AI technologies.
- Ensure data quality and integrity by developing tools and processes for monitoring and analyzing data accuracy and model performance.
- Lead data experiments under an iterative testing framework, ensuring continuous improvement in model performance.
- Collaborate closely with cross-functional teams to integrate GenAI models into existing infrastructure and to drive business solutions.
- Leverage predictive modeling techniques to enhance various business outcomes such as customer experience and revenue generation.
- Stay updated with the latest advancements in generative AI and integrate new knowledge into the company’s AI initiatives.
- Engage with stakeholders to understand their challenges and develop data-driven solutions.
- Communicate complex quantitative analysis clearly and precisely, providing actionable insights to stakeholders.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- 2+ years of experience in developing and implementing AI/ML models.
- Proficiency in Python and data querying languages such as SQL; familiarity with statistical/mathematical software like R is a plus.
- Experience with cloud infrastructures and platforms such as Azure, GCP, or AWS.
- Deep understanding of state-of-the-art generative AI models such as GPT-3, DALL-E, and CLIP.
- Experience with large-scale models training and evaluation on high-performance computing clusters.
- A robust understanding of deep learning, natural language processing, and computer vision.
- Excellent problem-solving skills with the ability to work both independently and in a team environment.
Preferred Qualifications
- Bachelor's or master's degree in a field such as Data Science, Statistics, Math, Physics, demonstrating strong groundwork in AI/ML.
- Demonstrated experience in developing and training AI models, especially in a production environment.
- Deep expertise in the concepts of deep learning, natural language processing, and computer vision.
- Experience in scaling generative models and deploying them in production environments.
- Capacity to collaborate effectively in a team environment and communicate complex technical concepts to non-technical stakeholders.