Junior AI Engineer

Role Overview

high-potential Junior AI Engineers

If you are excited about shipping AI into production, working with modern NLP and LLMs, and being accountable for outcomesnot just experimentsthis role is for you.

What You Will Do

Build & Ship AI Features

• Implement and improve AI models for exam evaluation and grading.
• Work on NLP problems such as answer similarity, rubric alignment, and feedback generation.
• Apply and fine-tune pre-trained models and LLMs for real-world education use cases.
• Rapidly prototype, test, and iterate on AI solutions with measurable impact.

Own Your Work End-to-End

• Take ownership of small to medium AI features from development to deployment.
• Write production-quality Python code with tests and documentation.
• Analyze model performance, identify issues, and drive improvements.
• Collaborate closely with backend engineers to deploy models as scalable services.

Operate Like a Startup Engineer

• Work with imperfect data and evolving requirements.
• Make trade-offs between accuracy, latency, and cost.
• Move fast while maintaining, quality and reliability.
• Learn continuously and apply feedback quickly.

Required Qualifications

• Strong proficiency in

  Python

  .
• Solid fundamentals in

  machine learning and NLP

  (through coursework, projects, or internships).
• Hands-on experience with at least one ML framework.
• Ability to understand, modify, and improve existing ML models.
• Comfortable reading research papers, documentation, and production code.
• Strong problem-solving skills and ownership mindset.

Strongly Preferred

• Personal, academic, or internship projects involving

  NLP or LLMs

  .
• Experience using embeddings, or prompt engineering.
• Familiarity with APIs, backend services, or cloud deployments.
• Participation in hackathons, competitions, or open-source contributions.
• Demonstrated ability to build something end-to-end and ship it.

What We Offer

• Real ownership and responsibility early in your career.
• Direct mentorship from senior AI and product leaders.
• Exposure to modern AI systems, including LLM-based architectures.
• Competitive compensation for high-performing junior talent in India.
• Fast career growth based on performance, not tenure.