ML Engineer

Position: ML Engineer/Data Scientist

Notice Period: Immediate Joiner

Experience: 5+ Years

Key Responsibilities

•  Collect, clean, and preprocess data from diverse sources to ensure quality and
• accuracy.
•  Develop and refine statistical models and Machine Learning (ML) algorithms to solve real-world problems.
•  Collaborate with cross-functional teams (e.g., data engineering, product, and business) to identify and understand analytical needs.
•  Perform exploratory data analysis (EDA) to uncover patterns, trends, and relationships in datasets.
•  Evaluate model performance using appropriate metrics, and iterate to optimize accuracy and efficiency.
•  Document analyses, methodologies, and best practices to maintain clear records for
• future reference.
•  Stay up-to-date with emerging AI/ML technologies and actively explore new
• approaches—especially in the areas of deep learning, Generative AI, and Large
• Language Models (LLMs).
•  Present findings and insights to both technical and non-technical stakeholders in a clear, concise manner.

Qualifications

•  Design and Build Data Pipelines: Assist in the development of reliable, efficient
• ETL (Extract, Transform, Load) and/or ELT pipelines that move data from a variety
• of internal and external sources into data storage systems.
•  Data Integration and Collaboration: Work closely with data scientists, data
• analysts, and software engineers to ensure data is readily available and properly
• structured for analysis and modeling.
•  Data Quality and Validation: Implement quality checks, error handling, and
• monitoring processes to ensure the reliability and accuracy of data.
•  Optimize Performance: Contribute to the optimization of data pipelines and
• database queries to handle high-volume data and achieve better performance and
• scalability.
•  Maintain Documentation: Develop and maintain technical documentation for data
• systems, pipelines, and processes to keep the team aligned and informed.
•  Security and Compliance: Support efforts to ensure secure data handling and
• compliance with relevant regulations and industry best practices.
•  Continuous Learning and Innovation: Stay informed about emerging data
• engineering tools, techniques, and technologies; share learnings with the team; and
• implement improvements where applicable
• Skills: llm,algorithms,machine learning,ai/ml,python,sql,data scientist,deep learning,eda,generative ai,ml,genai