Neo Group - Junior Machine Learning Engineer - Data Structure/Algorithm

Education Qualifications

• Bachelor's or master's degree in engineering, Information Technology, Computer Science, Technology, Mathematics, or Statistics (BE/ME/M.Tech/B.Tech/MSc IT/Equivalent).
  

Core Skills & Experience (Must-Have)

• Programming: Strong proficiency in Python with good knowledge of Data Structures & Algorithms (DSA).
• Machine Learning: 1+ years of experience in implementing ML models and algorithms.
• Statistics: Solid understanding of statistical concepts applied to data modeling.
• Databases: Hands-on experience with MongoDB and MySQL.
• Version Control: Practical experience with Git / Bitbucket.
• Project Management Tools: Exposure to JIRA or Asana.
  

Good To Have (Preferred Skills)

• Natural Language Processing (NLP) :
• Hands-on experience with Zero-shot / Few-shot classification algorithms.
• Familiarity with TF-IDF, Word2Vec, BERT for NLP-based tasks.
  

Generative AI

• Practical experience with OpenAI models (GPT series, etc.) and LLaMA for Generative AI applications.
• Web Development & APIs :
• Exposure to Flask and ability to build and deploy REST APIs.
  

Key Responsibilities

• Design, implement, and optimize Machine Learning / AI models for business use cases.
• Develop and fine-tune NLP-based solutions including text classification, embeddings, and semantic searches.
• Work with Generative AI frameworks to build prototypes and deploy AI-driven solutions.
• Collaborate with cross-functional teams to integrate AI/ML solutions into applications using Flask & REST APIs.
• Manage workflows using Git/Bitbucket and task tracking tools like JIRA/Asana.
• Work with relational & NoSQL databases (MySQL & MongoDB) for data preparation and model training.
• Continuously research and explore new techniques in ML, NLP, and Generative AI to improve solutions and models.
  

What We're Looking For

• A driven and curious mindset with the ability to quickly adapt to new technologies.
• Passion for AI research and its real-world applications.
• Strong analytical and problem-solving skills.
• Ability to work collaboratively in cross-functional teams.