Our client is a leading, innovative, and driven organization, pioneering advanced AI capabilities across their ecosystem. They are searching for a Data Scientist Generative AI to drive end-to end AI initiatives, from LLM development and RAG frameworks to scalable deployment and data pipeline engineering. This isnt support work, its transformation at an enterprise level.
Key Responsibilities :
- Design, develop, and optimize Generative AI models for operational and analytical use
- Build and fine-tune RAG frameworks using tools like LangChain, LlamaIndex, and other LLM platforms
- Engineer scalable data pipelines and perform ETL to support AI model training and deployment
- Collaborate with data and DevOps teams to deploy AI solutions in production environments
- Integrate data from multiple sources and ensure robust data warehousing and accessibility
- Drive performance, scalability, and cost efficiency for AI models in cloud and on-prem settings
- Communicate complex AI concepts to non-technical stakeholders and align work to business goals
- Continuously research, experiment, and stay ahead of GenAI trends and architectures
Job Experience and Skills Required :
3+ years in AI / ML, with at least 12 years focused on Generative AIStrong background in data engineering, ETL processes, and pipeline developmentHands-on experience with TensorFlow, PyTorch, and GenAI frameworksProficiency in Python, SQL, Pandas, and NumPyExperience with cloud platforms (AWS, GCP, and Azure) and container tools (Docker and Kubernetes)Knowledge of MLOps practices, including model versioning, monitoring, and retrainingFamiliarity with big data and storage tools like Spark, Hadoop, and vector databasesExcellent communication, teamwork, innovation mindset, and analytical problem-solvingBachelors Degree in Computer Science, Data Science, ML, or a related field (Masters / PhD advantageous)Preferred Certifications :AWS Certified Machine Learning / AI Practitioner
GCP ML Engineer or Cloud EngineerMicrosoft Azure AI Engineer / Data ScienceApply now!
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