AI/LLM Architect

What will you do

• Lead and participate in collaborative solutioning sessions with business stakeholders, translating business requirements and challenges into well-defined machine learning/data science use cases and comprehensive AI solution specifications.

• Architect robust and scalable AI solutions that enable data-driven decision-making, leveraging a deep understanding of statistical modeling, machine learning, and deep learning techniques to forecast business outcomes and optimize performance.

• Design and implement data integration strategies to unify and streamline diverse data sources, creating a consistent and cohesive data landscape for AI model development.

• Develop efficient and programmatic methods for synthesizing large volumes of data, extracting relevant features, and preparing data for AI model training and validation.

• Leverage advanced feature engineering techniques and quantitative methods, including statistical modeling, machine learning, deep learning, and generative AI, to implement, validate , and optimize AI models for accuracy, reliability, and performance.

• Simplify data presentation to help stakeholders easily grasp insights and make informed decisions.

• Maintain a deep understanding of the latest advancements in AI and generative AI, including various model architectures, training methodologies, and evaluation metrics . Identify opportunities to leverage generative AI to securely and ethically address business needs, optimize existing processes, and drive innovation .

• Contribute to project management processes, providing regular status updates, and ensuring the t imely delivery of high-quality AI solutions.

• Primarily responsible for contributing to project delivery and maximizing business impact through effective AI solution architecture and implementation . Occasionally contribute technical expertis e during pre-sales engagements and support internal operational improvements as needed.
  

What do you bring to the table

• A bachelors or masters degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering) is required . The ideal candidate will have a strong background in designing and implementing end-to-end AI/ML pipelines, including feature engineering, model training, and inference. Experience with Generative AI pipelines is needed .

• 8+ years of experience in AI/ML development, with at least 3+ years in an AI architecture role.

• Fluency in Python and SQL and noSQL is essential. Experience with common data science libraries such as pandas and Scikit-learn, as well as deep learning frameworks like PyTorch and TensorFlow, is required.

• Hands-on experience with cloud-based AI/ML platforms and tools, such as AWS (SageMaker, Bedrock), GCP (Vertex AI, Gemini), Azure AI Studio, or OpenAI, is a must . This includes experience with deploying and managing models in the cloud.