Data Scientist(6)

About this opportunity:

We are seeking a highly skilled, hands-on AI Architect - GenAI to lead the design and implementation of production-grade, cloud-native AI and NLP solutions that drive business value and enhance decision-making processes. The ideal candidate will have a robust background in machine learning, generative AI, and the architecture of scalable production systems. As an AI Architect, you will play a key role in shaping the direction of advanced AI technologies and leading teams in the development of cutting-edge solutions.

What you will do:

Architect and design AI and NLP solutions to address complex business challenges and support strategic decision-making.
Lead the design and development of scalable machine learning models and applications using Python, Spark, NoSQL databases, and other advanced technologies. Spearhead the integration of Generative AI techniques in production systems to deliver innovative solutions such as chatbots, automated document generation, and workflow optimization. Guide teams in conducting comprehensive data analysis and exploration to extract actionable insights from large datasets, ensuring these findings are communicated effectively to stakeholders. Collaborate with cross-functional teams, including software engineers and data engineers, to integrate AI models into production environments, ensuring scalability, reliability, and performance. Stay at the forefront of advancements in AI, NLP, and Generative AI, incorporating emerging methodologies into existing models and developing new algorithms to solve complex challenges. Provide thought leadership on best practices for AI model architecture, deployment, and continuous optimization. Ensure that AI solutions are built with scalability, reliability, and compliance in mind.

The skills you bring:

Minimum of experience in AI, machine learning, or a similar role, with a proven track record of delivering AI-driven solutions.
Hands-on experience in designing and implementing end-to-end GenAI-based solutions, particularly in chatbots, document generation, workflow automation, and other generative use cases. Expertise in Python programming and extensive experience with AI frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, and vector databases. Deep understanding and experience with distributed data processing using Spark. Proven experience in architecting, deploying, and optimizing machine learning models in production environments at scale. Expertise in working with open-source Generative AI models (e.g., GPT-4, Mistral, Code-Llama, StarCoder) and applying them to real-world use cases. Expertise in designing cloud-native architectures and microservices for AI/ML applications.