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Responsibilities
- Design, develop, and deploy AI/ML models using Python.
- Build traditional ML pipelines, including data preprocessing, feature engineering, model training, and evaluation.
- Create and fine-tune models using structured and unstructured data.
- Work on prompt engineering for LLM-based use cases and enhance model performance.
- Collaborate with backend teams to integrate ML models into applications and APIs.
- Optimize systems for scalability, performance, and reliability.
- Write clean, reusable, and production-grade code in Python (and occasionally PHP).
- Conduct experiments, model validation, and continuous performance improvements.
- Work closely with data teams to ensure robust data modeling and data quality.
- Document approaches, workflows, and technical designs.
- 2-5 years of hands-on experience in AI/ML development.
- Strong proficiency in Python with experience in ML/AI libraries (NumPy, pandas, scikit-learn, TensorFlow/PyTorch optional).
- Solid understanding of traditional machine learning techniques such as regression, classification, clustering, and feature engineering.
- Experience in building ML models from scratch using available datasets.
- Good knowledge of prompt engineering and working with LLMs is preferred.
- Knowledge of PHP (basic to intermediate) will be useful for certain integration tasks.
- Understanding of data modeling, data pipelines, and data preprocessing.
- Strong backend engineering mindset, ability to work with APIs, microservices, and production code.
- Experience in scaling ML systems, optimizing performance, and working with large datasets.
Key Skills
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