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7 Edureify Jobs
AI Engineer
Edureify
posted 3mon ago
Job Role Insights
Fixed timing
Key skills for the job
Job Description
We are seeking a passionate and innovative AI Engineer to design, develop, and deploy AI-driven solutions for our platform. As an AI Engineer, you will work on building intelligent systems that enhance user engagement, provide personalized learning experiences, and drive our mission to democratize coding education.
- Design, train, and optimize machine learning (ML) and deep learning (DL) models for use cases such as: Real-time (Coding co-pilot) code suggestions and debugging.
- Conversational AI for mentorship and learning guidance.
- Code generation and review tools.
- Develop algorithms for recommendation systems to personalize user experiences.
- Build efficient NLP and NLU pipelines for understanding coding queries.
- Implement solutions for automated error detection and resolution in code.
- Collaborate with software engineers to integrate AI models into the Edureify platform.
- Deploy models in a scalable and reliable manner using tools like Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
- Monitor model performance post-deployment and implement updates for continuous improvement.
- Design and maintain data pipelines to collect, preprocess, and annotate data.
- Work with big data frameworks (e.g., Hadoop, Spark) to handle large-scale datasets.
- Collaborate with cross-functional teams (product, engineering, design) to align AI functionalities with user needs.
- Stay updated on the latest AI trends, tools, and frameworks, and evaluate their potential for integration.
- Education: Bachelor s/Master s degree in Computer Science, Data Science, AI, or related fields.
- Experience: 3-5 years in AI/ML development, with a proven track record of deploying AI models in production.
- Programming: Proficiency in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn.
- NLP Expertise: Experience in natural language processing (NLP) and working with LLMs.
- Data Engineering: Strong understanding of data preprocessing, feature engineering, and working with structured and unstructured data.
- Cloud Proficiency: Hands-on experience with cloud-based AI/ML services (AWS SageMaker, Google AI, Azure ML).
- Knowledge of DevOps practices for AI model deployment.
- Familiarity with MLOps frameworks and tools (e.g., MLflow, Kubeflow).
- Expertise in Reinforcement Learning (RL) and its application in interactive systems.
Employment Type: Full Time, Permanent
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Strict timing
Monday to Saturday
No travel
Day Shift
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