GenAI Architect

Job Description

Role: GenAI Architect

Duration: long term

Roles and Responsibilities:

• 8-10 years of experience in developing Data Science, AI, and ML solutions, with a specific focus on generative AI and LLMs in the Finance/Telecomm/LSH/Manufacturing/Retail domain.
• Prior experience in identifying new opportunities to optimize business through analytics, AI/ML, and use case prioritization.
• The individual should be a thought leader having a well-balanced analytical business acumen, domain, and technical expertise.
• Large Model Expertise: Experience in working with and fine-tuning Large Models (LLMs), including the design and optimization of NLP systems, frameworks, and tools.
• Application Development with LLMs: Experience in building scalable applications using LLMs, utilizing frameworks such as LangChain, LlamaIndex, etc., and productionizing machine learning and AI models.
• Model Development: Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications.
• Cloud Computing Expertise: Proven architect-level experience in cloud computing, particularly with Azure Cloud Services.
• Technical Proficiency: Strong skills in UNIX/Linux environments and command-line tools.
• Programming and ML Skills: Proficiency in Python, with a deep understanding of machine learning algorithms, deep learning, and generative models.
• Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing of developed AI components.
• Responsibilities also include data analysis/preprocessing for training and fine-tuning models. Additionally, the role involves solving issues around privacy, real-time data collection, sparse data collection, passive data collection, and compliance with security and regulatory requirements.

Educational Qualifications:

Graduate or Doctorate degree in information technology, Neuroscience, Business Informatics, Biomedical Engineering, Computer Science, Artificial Intelligence, or a related field.

Specialization in Natural Language Processing is preferred.

#J-18808-Ljbffr