AI/ML Lead

Key Responsibilities

• Hands-On Execution and Delivery: Actively contribute to the development and delivery of AI solutions, driving innovation and excellence within the team. Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks.
• Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation.
• Research and Development: Participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field.
• Cross-Functional Collaboration: Collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services.
  

Skills & Qualifications

• Strong hands-on experience in Machine Learning, delivering complex solutions to production.
• Experience with Generative AI technologies essential.
• In-depth knowledge of deep learning and Generative AI frameworks such as TensorFlow, PyTorch, Langchain, Lang Graph, Crew AI or similar.
• Experience with and other open-source frameworks/ libraries/ APIs like Hugging Face Transformers, Spacy, Pandas.\
• Proficiency in Python Software Development, following Object-Oriented design patterns and best practices.
• Experience with evaluation, scoring with framework like ML Flow
• Experience of Docker container and edited a Docker file, experience with K8s is a plus.
• Experience with Postgres and Vector DBs a plus.
• Excellent problem-solving skills and the ability to think creatively.
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
• Publications and contributions to the AI research community are a plus.
• Bachelor/Master degree or equivalent experience in Computer Science, Data Science, Statistics, or a related field.