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AI & Data Scientist (Agentic AI / ML Engineer) Intern Job Sybyl
IT Jobs. Sybyl Jobs
Role Overview.
Sybyl is seeking a hands-on AI & Data Scientist to design, develop, and deploy intelligent AI solutions across enterprise systems. The role focuses on Agentic AI, LLM fine-tuning, RAG systems, feature engineering, AutoML, and scalable data pipelines — particularly within regulated industries such as Banking and Financial Services (BFSI). Practical experience and proven skills are more important than academic qualifications.
Responsibilities
- Design and deploy AI agents for business process automation.
- Build multi-agent systems and orchestration frameworks.
- Fine-tune open-source LLMs (e.g., Mistral, Qwen, LLaMA)
- Develop Retrieval-Augmented Generation (RAG) systems using vector databases.
- Implement prompt engineering and production-grade AI pipelines.
- Perform data preprocessing, EDA, and statistical analysis.
- Develop predictive ML models and optimize features.
- Define evaluation metrics and ensure model performance.
- Implement explainability and compliance-ready documentation.
- Deploy models as APIs with real-time scoring.
- Build auditable feature pipelines with data lineage tracking.
- Develop reusable, governed feature sets for production.
- Integrate with banking systems, credit bureaus, LOS, LMS.
- Implement data quality validation frameworks.
- Build ETL/ELT pipelines using PySpark and distributed systems.
- Work with SQL/NoSQL databases.
- Implement CI/CD pipelines for ML deployment.
- Monitor, version, and maintain production models.
- Work closely with AI, BI, RPA, and business teams.
- Document experiments, models, and technical solutions.
- Present insights and recommendations to stakeholders.
Qualifications
- Strong Python proficiency (pandas, NumPy, scikit-learn)
- Experience with PySpark and SQL
- Hands-on experience with LLM fine-tuning, RAG systems, and vector databases
- Solid understanding of ML algorithms, feature engineering, and data governance
- Experience with Git and Jupyter environments
Candidate Profile
- Experience with Agentic AI and multi-agent systems
- AutoML, MLOps, and Explainable AI (XAI) knowledge
- Experience in BFSI domain (banking, credit bureaus, financial systems)
- Cloud experience (AWS, GCP, Azure)
- Portfolio of AI/ML projects or open-source contributions
How to Apply
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