AI Engineer / Machine Learning Engineer

•Algorithm Development - Design, build, and optimize machine learning algorithms and models for various HR-related applications, such as candidate screening, talent matching, performance prediction, and sentiment analysis.
•Cloud Infrastructure - Architect, develop, and deploy AI-related cloud infrastructure and services on platforms like AWS, Azure, or Google Cloud Platform. This includes setting up and managing data pipelines, model serving endpoints, and scalable computing resources.
•Full Lifecycle Development - Take ownership of the entire machine learning lifecycle, from initial data exploration and feature engineering to model training, evaluation, and deployment in a production environment.
•Collaboration - Work closely with product managers, data scientists, and other software engineers to understand business requirements, translate them into technical specifications, and deliver high-quality, impactful solutions.
•Performance & Optimization - Monitor the performance of deployed models, troubleshoot issues, and continuously improve algorithms to enhance accuracy and
efficiency.
•Research & Innovation - Stay up-to-date with the latest advancements in AI, machine learning, and cloud technologies. Propose and experiment with new tools and techniques to keep our products at the forefront of the industry.
•Code Quality - Write clean, well-documented, and maintainable code, adhering to best practices in software development.

• Age : 25-35
• Pre intermediate English
•2+ years of professional hands-on experience as an AI Developer, Machine Learning Engineer, or similar role.
•Hands-on experience with cloud platforms (AWS, or GCP) and related services (e.g., S3, EC2, Lambda, SageMaker, Google AI Platform).
•Solid understanding of machine learning principles, including supervised, unsupervised, and reinforcement learning.
•Strong programming skills in implementing programs using Python.
•Development experience with database technologies (SQL and NoSQL) and relational databases
Preferable:
•Development experience using git, Jupyter notebook, and cloud
•Experience with containerization technologies (e.g., Docker, Kubernetes).
•Experienced growth in business using data AI
•Experience with project leads with multiple members