Description
We are looking for a
hands-on AI/ML Engineer with
strong skills in Python, traditional machine learning, and backend-oriented model development. The ideal candidate should be comfortable with prompt engineering, building scalable ML systems, and integrating models into production :
- 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.
Requirements
- 2-5 years of hands-on experience in AI/ML 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.
(ref:hirist.tech)
