Data Scientist ( AI Specialist )We are seeking a skilled AI Practitioner/Data Scientist with a deep specialization in Generative AI and a robust background in data. The ideal candidate will have hands-on experience in designing, developing, and deploying AI models with a focus on generative techniques. This role demands a strong understanding of data engineering principles, making the candidate well-equipped to handle the data pipeline challenges inherent in AI and data projects.
GenAI Model Development:Design, implement, and optimize operational and analytical solutions utilizing Generative AI models.Develop and fine-tune RAG (Retrieval Augmented Generation) frameworks utilizing LLM frameworks such as LangChain, Llama-Index or other generative frameworks.Experiment with new architectures and techniques to push the boundaries of generative AI.Data Engineering:Collaborate with data engineering/analyst teams to ensure the availability and quality of data needed for model training and validation.Design and maintain scalable data pipelines to handle large volumes of structured and unstructured data.Perform ETL tasks to create optimal data-warehousing structures (Dimensional modelling) for optimal storage, ease of use and maintainability.Integrate data from various sources and ensure its proper storage, transformation, and accessibility.Deployment and Scaling:Deploy AI and generative AI models in production environments, ensuring they meet performance, scalability, and reliability requirements.Work with DevOps teams to automate the deployment and monitoring of AI models.Optimize model inference for performance and cost efficiency in cloud and on-premises environments.Collaboration and Communication:Collaborate with cross-functional teams, including data scientists, engineers, product managers, and business stakeholders, to align AI solutions with business objectives.Communicate complex AI concepts and findings to non-technical stakeholders.Continuous Learning and Innovation:Stay up to date with the latest advancements in Generative AI and data engineering.Participate in conferences, workshops, and other professional development opportunities.Contribute to research publications and patent filings in the field of Generative AI.Requirements3+ years of experience in AI, with a focus on Generative AI (1-2 years).Proven experience in data engineering, including data pipeline development, ETL processes, and database management.Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and Generative AI frameworks.Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).Technical Skills:Proficiency in programming languages such as Python, SQL, and familiarity with data manipulation libraries (e.g., Pandas, NumPy).Strong knowledge of machine learning algorithms, neural networks, and generative models.Experience with data storage solutions (e.g., Hadoop, Spark, Vector databases).Knowledge of MLOps practices, including model versioning, monitoring, and retraining.Soft Skills:A proactive attitude with a passion for learning and innovation.Excellent communication and teamwork abilities.Strong problem-solving and analytical skills.Preferred Qualifications and CertificationBachelor's or master's degree in Computer Science, Data Science, Machine Learning, or a related field.Master's or Ph.D. is advantageous.Any of the following certifications are highly advised:AWS Certified AI PractitionerAWS Certified Machine LearningGCP Professional Machine Learning EngineerGCP Associate Cloud EngineerMicrosoft Azure AI engineerMicrosoft Azure Data Science.
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