• 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.

Must

• 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