AI Solution Architect

Role : AI Solution Architect

JD :

As an AI/ML Solution Architect, you will be responsible for designing and overseeing the architecture of AI and machine learning solutions. You will work closely with data scientists, MLOps team, engineers, and business stakeholders to ensure that our AI/ML initiatives are scalable, robust, and aligned with business objectives. Your expertise in machine learning, deep learning, natural language processing (NLP), and generative AI will be crucial in guiding the development and deployment of advanced AI solutions.

Responsibilities:

• Design and architect end-to-end AI/ML solutions that meet business requirements and technical specifications.

• Develop and implement scalable machine learning and deep learning models, ensuring they integrate seamlessly into existing systems.

• Create architectures for NLP applications, including text processing, sentiment analysis, named entity recognition, and language modelling.

• Leverage generative AI and large language models (LLMs) to develop innovative applications.

• Collaborate with data engineers to design data pipelines and ensure data quality and accessibility.

• Provide technical leadership and guidance to data scientists and engineers throughout the development lifecycle.

• Evaluate and select appropriate AI/ML tools, frameworks, and technologies to meet project needs.

• Ensure best practices in AI/ML model development, including versioning, testing, and validation. • Stay updated with the latest advancements in AI/ML technologies and incorporate them into architectural designs.

• Communicate complex AI/ML concepts and solutions effectively to non-technical stakeholders.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field with proven experience (8+ years) in designing and implementing AI/ML solutions, with a strong focus on machine learning, deep learning, NLP, and generative AI.

• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, and Keras and experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services.

• Strong expertise in NLP techniques and tools, including experience with LLMs like Gemini, GPT, BERT, etc. • Strong communication skills, with the ability to present technical concepts to both technical and non-technical audiences and experience in leading and mentoring technical teams.

• Experience with MLOps practices and tools for continuous integration and deployment of machine learning models.