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Data Scientist (Gen AI)
Bengaluru · Senior
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Job description
- Architect, build, and deploy scalable GenAI applications using OpenAI, and Retrieval-Augmented Generation (RAG) techniques.
- Design and orchestrate modular, reproducible, and robust data pipelines leveraging Kedro for end-to-end machine learning workflows.
- Integrate LangChain to develop advanced natural language workflows and enhance AI-powered applications.
- Take GenAI prototypes from concept to production, ensuring reliability, scalability, and maintainability in real-world environments.
- Containerize machine learning and GenAI solutions with Docker for seamless deployment and scalability across cloud and on-premises platforms.
- Collaborate with cross-functional teams—including Engineering, Product, and Operations—to align AI solutions with business goals and deliver measurable impact.
- Mentor and support junior team members, sharing best practices in data science, MLOps, and GenAI deployment.
- Continuously evaluate and implement emerging AI technologies, driving innovation and excellence in our AI capabilities.
- 4+ years of experience in GenAI, data science, machine learning, or AI-focused roles. 2+ years of experience in GenAI.
- Advanced proficiency in Python; extensive experience with OpenAI APIs, and other modern LLMs.
- Strong background in Retrieval-Augmented Generation (RAG) methods and architectures.
- Proven expertise with LangChain for natural language processing and workflow automation.
- Demonstrated experience taking GenAI prototypes to production environments.
- Experience building and orchestrating data pipelines with Kedro.
- Proficient in Docker-based containerization and deployment (Kubernetes a plus).
- Knowledge of data engineering and software engineering best practices.
- Excellent communication, collaboration, and mentoring skills.
- Bachelor’s or master’s degree in computer science, Data Science, Engineering, or a related field.
- Experience with working on SQL DB like Postgres and No-SQL DB like MongoDB
- Experience with AWS or other major cloud platforms.
- Experience with CI/CD tools and automated testing frameworks.
- Open-source contributions, technical presentations, or publications in AI/ML.
- Previous leadership or mentorship of technical teams.
- Building Backend Python APIs
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