Key Responsibilities :

- Design, develop, and maintain scalable, efficient, and reliable systems to support GenAI and machine learning-based applications and use cases

- Lead the development of data pipelines, architectures, and tools to support data-intensive projects, ensuring high performance, security, and compliance

- Collaborate with other stakeholders to integrate AI and ML models into production-ready systems

- Work closely with non-backend expert counterparts, such as data scientists and ML engineers, to ensure seamless integration of AI and ML models into backend systems

- Ensure high-quality code, following best practices, and adhering to industry standards and company guidelines

Hard Requirements :

- Senior backend engineer with a proven track record of owning the backend portion of projects

- Experience collaborating with product, project, and domain team members

- Strong understanding of data pipelines, architectures, and tools

- Proficiency in Python (ability to read, write and debug Python code with minimal guidance)

Mandatory Skills :

- Machine Learning : experience with machine learning frameworks, such as scikit-learn, TensorFlow, or PyTorch

- Python : proficiency in Python programming, with experience working with libraries and frameworks, such as NumPy, pandas, and Flask

- Natural Language Processing : experience with NLP techniques, such as text processing, sentiment analysis, and topic modeling

- Deep Learning : experience with deep learning frameworks, such as TensorFlow, or PyTorch

- Data Science : experience working with data science tools

- Backend : experience with backend development, including design, development, and deployment of scalable and modular systems

- Artificial Intelligence : experience with AI concepts, including computer vision, robotics, and expert systems

- Pattern Recognition : experience with pattern recognition techniques, such as clustering, classification, and regression

- Statistical Modeling : experience with statistical modeling, including hypothesis testing, confidence intervals, and regression analysis