- We are seeking a skilled and motivated AI and Machine Learning Developer to advance machine learning initiatives focused on quiz generation and scenario-based knowledge assessments.

- This role will be responsible for maintaining and enhancing existing ML solutions while contributing to the continuous evolution of the clients learning and engagement products.

- The ideal candidate combines strong machine learning fundamentals with hands-on experience in NLP, data pipelines, and model optimization, and is comfortable collaborating with cross-functional product, UX, and content teams.

Key Responsibilities:

- Design, develop, maintain, and enhance machine learning models for personalized quiz generation and scenario-based assessments.

- Build, manage, and optimize data pipelines, including data collection, preprocessing, validation, and feature engineering to ensure high-quality model inputs.

- Collaborate closely with educational content creators and subject matter experts to ensure generated quizzes and scenarios are accurate, relevant, and aligned with defined learning objectives.

- Work with UX and UI teams to support the development and refinement of interactive, user-friendly quiz and scenario-based experiences.

- Monitor, evaluate, and fine-tune existing models to improve accuracy, performance, scalability, and user engagement.

- Conduct experiments, including A/B testing, and analyze user behavior and feedback to drive continuous model and product improvement.

- Implement best practices for model evaluation, versioning, deployment, and monitoring in production environments.

- Stay up to date with advancements in machine learning, NLP, generative AI, and educational technology, and apply relevant innovations to strengthen the platform.

Required Skills & Qualifications:

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.

- Minimum 3 Years of strong hands-on experience with machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

- Practical experience in Natural Language Processing (NLP), particularly text generation, classification, or semantic analysis.

- Proficiency in Python and experience working with ML-oriented data processing libraries (NumPy, pandas, etc.).

- Experience designing and maintaining data pipelines and working with structured and unstructured data.

- Familiarity with model evaluation techniques, experimentation frameworks, and A/B testing methodologies.

- Understanding of ML model deployment and integration into production systems (APIs, cloud platforms, or MLOps pipelines).

- Strong problem-solving skills and ability to work collaboratively in cross-functional teams.

- Good communication skills, with the ability to explain technical concepts to non-technical stakeholders.