AI/ML Engineer

JD For Junior Data Scientist

Junior Data Scientist with a specialization in Generative AI. The ideal candidate will be enthusiastic about exploring new problems, driving innovation, and leveraging advanced machine learning techniques and programming skills (especially in Python). You will assist in enhancing the analytics backend flagship products and contribute to advancing knowledge discovery solutions. This role is perfect for someone who enjoys learning, creative problem-solving, and working in a dynamic environment.

Eligibility

•        Minimum Qualifications: • Bachelors degree in computer science or a related field OR master's degree in statistics

•        2-6 years of experience in the Analytics/Data Science domain.

•        Proficiency in programming languages such as Python.

•        Experience with Generative AI techniques and tools.

•        Familiarity with data imputation, data cleaning, and outlier handling.

•        Familiarity with cloud platforms AWS and AI/ML services.

•        Knowledge of databases and associated tools such as SQL.

Technical Skills – Desirable:

•        Expertise in NLP and Generative AI concepts/methods/techniques like

—    Prompt design/engineering

—    Retrieval Augmented Generation (RAG), Corrective RAG and Knowledge Graph-based RAG using GPT4o

—    Fine-tuning through LORA/QLORA

—    Multi-agentic frameworks for RAG

•        Strong understanding of Deep Learning methods and Machine Learning techniques including Ensemble methods, Support Vector Machines, and Natural Language Processing (NLP).

Specific Responsibilities

•        Requirement Gathering:

o  Translate business requirements into actionable analytical plans in collaboration with the team.

o  Ensure alignment of analytical plans with the customer's strategic objectives.

•        Data Handling:

o  Identify and leverage appropriate data sources to address business problems.

o  Explore, diagnose, and resolve data discrepancies, missing values, and outliers.

•        Development and Execution:

—    Individually deliver projects, proof-of-concept (POC) initiatives from inception to completion.

—    Contribute to the development and refinement of technical and analytics architecture, ensuring it aligns with project and organizational goals.

—    Implement scalable and robust analytical frameworks and data pipelines to support advanced analytics and machine learning applications.

—    Coordinating with cross-functional teams to achieve project goals.

—    Delivery of production-ready models and solutions, meeting quality and performance standards.

—    Monitor success metrics to ensure high-quality output and make necessary adjustments.

—    Create and maintain documentation/reports.

Innovation and Best Practices:

•        Stay informed about new trends in Generative AI and integrate relevant advancements into our solutions.

Implement novel applications of Generative AI algorithms and techniques in Python