Data Scientist- Gen AI and ML

Job Title:

Experience Required:

Location:

About the Role:

We are seeking a data scientist with around 3 years of experience in applied machine learning, data analytics, and GenAI solutions. The ideal candidate will have a strong foundation in traditional ML along with hands-on exposure to LLMs (Large Language Models), Retrieval-Augmented Generation (RAG) architectures, and prompt engineering. You’ll work on end-to-end data projects — from data collection and model training to deploying AI-driven applications that enhance decision-making and automation.

Key Responsibilities:

●      Analyze large datasets to generate actionable business insights.

●      Design, train, and optimize ML and GenAI models for tasks such as text generation, summarization, classification, and recommendation.

●      Develop and maintain RAG pipelines, integrating vector databases and retrieval layers to improve model accuracy and contextual awareness.

●      Implement and fine-tune LLMs using frameworks like LangChain, LlamaIndex, or Hugging Face Transformers.

●      Build data pipelines and automation workflows for scalable model deployment.

●      Collaborate with engineering teams to operationalize AI models using cloud services (AWS SageMaker, Azure ML, GCP Vertex AI).

●      Perform exploratory data analysis (EDA), feature engineering, and model evaluation using statistical and ML methods.

●      Visualize data and insights through tools like Tableau, Power BI, or Plotly Dash.

●      Document experiments, performance metrics, and maintain reproducibility of models.

●      Stay updated on the latest developments in GenAI, LLMs, and applied ML research.

Required Skills and Qualifications:

●      Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.

●      3+ years of experience as a Data Scientist, ML Engineer, or AI Researcher.

●      Strong proficiency in Python (pandas, numpy, scikit-learn, matplotlib, seaborn)

●      Solid understanding of machine learning algorithms, model evaluation, and data preprocessing.

●      Experience building or fine-tuning LLMs and implementing RAG pipelines.

●      Familiarity with GenAI frameworks (LangChain, LlamaIndex, OpenAI API, Hugging Face).

●      Experience with SQL and working with large, real-world datasets.

●      Exposure to cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).

●      Experience with version control (Git) and collaborative workflows.

Preferred Qualifications:

●      Knowledge of vector databases (Pinecone, FAISS, Weaviate, ChromaDB).

●      Experience with MLOps tools (MLflow, DVC, Kubeflow).

●      Understanding of prompt engineering and context optimization for LLMs.

●      Experience deploying chatbots, Q&A systems, or document intelligence solutions.

●      Strong business understanding with the ability to connect AI outcomes to business impact.

Soft Skills:

●      Excellent analytical and problem-solving skills.

●      Strong written and verbal communication for explaining technical concepts to non-technical teams.

●      Ability to work independently and in cross-functional teams.

●      Curiosity and passion for emerging AI technologies.