Job Overview
- Experience Level
- +3 years
- Employment Type
- Part-time
- Workplace Type
- Not specified
- Location
- Cairo
- Job function
- Not specified
- Application Deadline
- 29 December 2024
About the Role
Lead the design, development, and implementation of machine learning models and algorithms to solve complex business problems. Collaborate with software engineers, and domain experts to gather requirements, define project goals, and identify data sources. Conduct exploratory data analysis, data preprocessing, and feature engineering to prepare data for model training. Develop and implement scalable and efficient machine learning pipelines and workflows. Train, evaluate, and fine-tune machine learning models using state-of-the-art techniques and algorithms. Optimize and deploy machine learning models into production systems, ensuring high performance, scalability, and reliability. Conduct experiments and A/B testing to measure the performance and effectiveness of machine learning models. Stay up to date with the latest advancements in machine learning and related technologies and apply them to improve our machine learning capabilities. Mentor and provide guidance to junior members of the team, sharing best practices and knowledge. Collaborate with stakeholders to understand business requirements and translate them into technical solutions.
Requirements
Bachelor's degree in computer science, Engineering, or a related field. Proven professional experience as a Machine Learning Engineer, Data Scientist, or related role, with a focus on developing and deploying machine learning models. Strong programming skills in languages such as Python, R, or Java, with experience in data manipulation, analysis, and model development libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Solid understanding of machine learning algorithms, statistical modeling, and deep learning architectures. Experience with data preprocessing techniques, feature engineering, and model evaluation. Proficiency in working with large-scale datasets and distributed computing frameworks (e.g., Hadoop, Spark). Hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) and knowledge of deploying machine learning models to production. Strong problem-solving skills and the ability to apply analytical thinking to real-world challenges. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams. Proven ability to lead projects, mentor team members, and drive results in a fast-paced environment. Strong understanding of software engineering principles and best practices.