Junior Data Scientist – AI & Generative AI Engineer

About the role

We are seeking a Junior Data Scientist with a strong focus on AI and Generative AI to design, build and deploy intelligent solutions that address real business challenges. The role bridges data science, machine learning and modern LLM‑based technologies, working closely with stakeholders and engineering teams.

Key responsibilities

• Develop machine learning and Generative AI solutions for business use cases.
• Build models for prediction, classification, recommendation, forecasting, anomaly detection and NLP.
• Design Retrieval‑Augmented Generation (RAG) pipelines using embeddings, vector databases and large language models.
• Work with both structured and unstructured data sources.
• Create data and ML pipelines for training, evaluation, deployment and monitoring.
• Integrate AI models into APIs, applications and enterprise workflows.
• Evaluate model quality, reliability, cost, latency and business impact.
• Apply responsible AI practices, including privacy, security, explainability and human review.
• Collaborate with business, engineering and architecture teams throughout the project lifecycle.

Required profile

• 3–5 years of experience in data science, machine learning or AI engineering.
• Strong proficiency in Python and SQL.
• Hands‑on experience with scikit‑learn, XGBoost, PyTorch or TensorFlow.
• Experience in NLP, text analytics or document processing.
• Practical exposure to large language models, prompt engineering, embeddings, vector search and RAG.
• Familiarity with cloud platforms such as AWS, Azure or Google Cloud.
• Understanding of MLOps, CI/CD, model deployment and monitoring.
• Excellent communication and problem‑solving abilities.

Required skills

• Python
• SQL
• scikit‑learn
• XGBoost
• PyTorch
• TensorFlow
• NLP
• Large Language Models (LLMs)
• Prompt engineering
• Embeddings
• Vector search
• RAG pipelines
• AWS
• Azure
• Google Cloud
• MLOps
• CI/CD
• Model deployment
• Model monitoring