About the role
Requirements:
- Backend Engineering: Strong proficiency in Node.js and TypeScript/JavaScript, including API design, asynchronous processing, event-driven systems, and backend architecture.
- System Design: Demonstrated expertise in distributed systems, scalability, reliability, database design, caching, messaging, and system integration.
- AI/ML Engineering: Strong understanding of machine learning, deep learning, neural networks, transformer architectures, and LLM internals.
- LLM Training: Practical experience training LLMs from scratch and taking trained models through evaluation, optimization, and production deployment.
- ML Frameworks: Hands-on proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Data Engineering: Experience with data pipelines, dataset preparation, data quality, vector embeddings, and efficient data processing.
- LLM Systems: Working knowledge of tokenization, attention mechanisms, inference optimization, GPU utilization, model evaluation, and serving infrastructure.
- Infrastructure and Deployment: Experience with Docker, CI/CD, cloud or on-premises infrastructure, monitoring, logging, and production operations.
- Databases: Strong understanding of SQL and NoSQL databases, data modeling, query optimization, and performance tuning.
- Engineering Practices: Proficiency in automated testing, debugging, code reviews, version control, security, and maintainable software design.