Description

Build and optimize machine learning models for adaptive learning solutions. You will own the end-to-end lifecycle from algorithm design to production deployment.

Responsibilities

• Develop machine learning algorithms for skill assessment, content recommendation, and student progress tracking.
• Design data pipelines to collect, preprocess, and engineer features from large-scale educational datasets.
• Utilize large language models and generative AI to customize and generate new learning content.
• Train, validate, and optimize models in production environments while monitoring performance via learning analytics.
• Collaborate with cross-functional teams to define technical architecture and integrate AI features into user interfaces.

Required Skills

• 5+ years of experience in software engineering with a strong full-stack background.
• Proficiency in Python, Java, or C++.
• Experience with machine learning libraries including TensorFlow, PyTorch, or scikit-learn.
• Hands-on experience with LLMs (GPT-3, GPT-4) and frameworks such as LangChain, HuggingFace, LangFlow, or FlowiseAI.
• Deep understanding of supervised, unsupervised, deep learning, transformers, and reinforcement learning.
• Experience with cloud computing platforms including AWS, Azure, or GCP.
• Strong foundation in mathematics and statistics.
• Knowledge of distributed computing and open-source framework implications.

Preferred Skills

• Experience with cloud-based AI/ML services like AWS SageMaker, Google Cloud AI, or Azure ML.
• Working knowledge of NodeJS frameworks such as ReactJS, VueJS, or Svelte.
• Familiarity with agile methodologies and DevOps practices.

Key Skills

Education

Any Graduate