As a Generative AI Solution Architect, you will be at the forefront of leveraging Generative Artificial Intelligence technologies to design and implement innovative solutions. This role requires a deep understanding of generative AI algorithms, creative problem-solving skills, and the ability to collaborate with interdisciplinary teams to bring forth novel applications in diverse industries.
Responsibilities
- Define and articulate clear requirements for generative AI solutions based on business needs.
- Architect end-to-end solutions that leverage generative AI technologies.
- Approach solutions that could be POC led, Platform led or integrated end to end solution.
- Evaluate and select appropriate generative AI solutions and environment based on customer and project requirements.
- Finalization on estimations that are optimized from a performance, scale, efficiency and fits the business case.
- Integrate ethical considerations in to the solution design and deployment of generative AI solutions, addressing issues such as bias, fairness and responsible use.
Qualifications
- Ability to identify, attract, onboard, and train skills for execution of customer-led POCs and projects within agreed timelines.
- 8+ years of hands-on experience in a technical role, specifically focusing on generative AI, with a strong emphasis on training Large Language Models (LLMs).
- Proven track record of successfully deploying and optimizing LLM models for inference in production environments.
- In-depth understanding of state-of-the-art language models, including but not limited to GPT-3, BERT, or similar architectures.
- Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
- Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms, with a focus on GPUs.
- Strong knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference.