What do you need for this opportunity?
Digibee is Looking for a highly skilled and innovative Generative AI Engineer to join their dynamic team. As a Generative AI Engineer, you will play a key role in designing, implementing, and advancing state-of-the-art generative AI models. The successful candidate will collaborate with cross-functional teams, contributing to delivering cutting-edge AI functionalities in Digibee Integration Platform.
On a typical day, you will:
- Research, design, and develop innovative generative AI models and algorithms.
- Implement and optimize deep learning architectures for generative tasks, focused on text generation.
- Collaborate with cross-functional teams to define goals, requirements, and deliverables and implement the features.
- Train and fine-tune models using large-scale datasets and advanced techniques.
- Evaluate and assess model performance, making necessary adjustments to improve results.
- Stay up-to-date with the latest advancements in generative AI trends and tools and contribute to the team's knowledge base.
- Write clean, efficient, and maintainable code, following best practices and coding standards.
- Document research findings, methodologies, and technical specifications.
- Participate in code reviews and provide constructive feedback to peers.
- Contribute to the development of tools and frameworks to facilitate generative AI research and development.
- Interpret insights from our pre-sales, sales, customer success teams and clients to create AI-based features.
This Role Requires:
What You'll Need To Bring
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Advanced or fluent English language proficiency.
- Strong understanding of machine learning, deep learning, and generative models.
- Proficiency in Python, TensorFlow, PyTorch, and other deep-learning related tools.
- Familiarity with the Hugging Face Transformers library of pre-trained models, including GPT-2, BERT, and others.
- Experience developing and training deep learning models using large-scale datasets.
- Solid understanding of neural network architectures (CNN, RNN, LSTM, Transformers), optimization techniques, and loss functions.
- Familiarity with natural language processing (NLP) tools and frameworks.
- Strong problem-solving skills and ability to think creatively.
- Excellent communication and collaboration skills.
- Ability to work independently and manage multiple projects simultaneously.
Nice to have
- Proven experience on projects involving Large Language Models (LLMs) such as GPT, Bard, or LLaMA.
- Familiarity with data engineering and MLOps.
- Experience working with cloud platforms dedicated to training and deploying AI/ML projects such as SageMaker or Vertex AI.
- Master degree in Data Science related fields.
- Familiarity with graphs and GNN.