Generative AI Engineer

3 days ago

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Provision Global Procurement Services

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Procurement Services • Hospitality • Supply Chain • Development • Advisory

11 - 50 employees

🤝 B2B

Description

• Develop cutting-edge RAG models and large language models using advanced techniques in NLP, NLU, and NLG. • Collaborate with cross-functional teams to define AI project requirements, ensuring alignment with business goals. • Conduct research on the latest advancements in generative AI, machine learning, and deep learning to integrate new opportunities into our products. • Optimize existing generative AI models for performance, scalability, and efficiency. • Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation. • Prepare datasets and ensure they are AI-ready, with a focus on feature creation and alignment. • Create clear and concise documentation to communicate complex AI concepts to both technical and non-technical stakeholders. • Contribute to the establishment of best practices for generative AI development within the organization. • Provide technical mentorship and guidance to junior team members.

Requirements

• A degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. • Proficiency in Python, with experience in machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras. • Strong understanding of data structures, algorithms, and software engineering principles. • Familiarity with at least one cloud platform (GCP preferred, followed by AWS or Azure). • Experience with NLP techniques and tools, such as SpaCy, NLTK, or Hugging Face. • Familiarity with data visualization tools like Matplotlib, Seaborn, or Plotly. • Knowledge of software development methodologies, including Agile or Scrum. • Excellent problem-solving skills, with the ability to think critically and creatively to develop AI solutions. • Strong communication skills, able to convey complex technical concepts effectively to diverse audiences. • A proactive mindset, with the ability to work both independently and collaboratively in a fast-paced environment. • Experience developing and implementing generative AI models, with a deep understanding of techniques such as GPT, VAE, and GANs is optional. • Knowledge of Retrieval Interleaved Generation (RIG) is optional. • Experience with other NLP areas like sentiment analysis or chatbot development is optional. • Familiarity with MultiAgent GenAI or AutoGen is a plus but not mandatory.