AI/ML Engineer II job opportunity at Astreya.



DateMore Than 30 Days Ago bot
Astreya AI/ML Engineer II
Experience: 3-years
Pattern: full-time
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loacation Singapore, Singapore, Singapore
loacation Singapore, Sin..........Singapore

Job Summary We are seeking a highly motivated and experienced AI/ML Engineer Level 2 to join our innovative team. The successful candidate will be instrumental in designing, developing, and deploying cutting-edge artificial intelligence and machine learning solutions that drive our services forward. This role requires a strong understanding of machine learning principles, proficiency in relevant programming languages and frameworks, and the ability to work collaboratively in a fast-paced environment. Responsibilities Design, develop, and deploy machine learning models and algorithms. Work with large datasets to extract insights and build robust data pipelines. Collaborate with cross-functional teams to integrate AI/ML solutions into existing products and services. Optimize and fine-tune machine learning models for performance and scalability. Conduct research and stay up-to-date with the latest advancements in AI/ML. Participate in code reviews and contribute to maintaining high code quality. Troubleshoot and debug AI/ML systems and applications. Qualifications Required Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 3+ years of experience in AI/ML engineering or a similar role. Proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of machine learning algorithms, including supervised, unsupervised, and reinforcement learning. Experience with data preprocessing, feature engineering, and model evaluation. Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices. Excellent problem-solving skills and attention to detail. Strong communication and teamwork abilities. Preferred Experience with distributed computing frameworks (e.g., Spark, Hadoop). Knowledge of deep learning architectures and techniques. Experience with containerization technologies (e.g., Docker, Kubernetes). Contributions to open-source AI/ML projects.

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