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 10+ years 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.