Senior ML Engineer

Responsibilities: • Develop machine learning models and algorithms to address business needs. • Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions. • Clean, preprocess, and analyze large datasets to extract meaningful insights. • Deploy machine learning models into production environments and monitor their performance. • Continuously improve model accuracy and performance through experimentation and optimization. • Stay up-to-date with the latest advancements in machine learning and related technologies. • Communicate findings and results to stakeholders in a clear and concise manner. Requirements: • Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field. • 2~5 years of experience in machine learning, data science, or a related field. • Proficiency in programming languages such as Python, Java, or Scala. • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. • Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning. • Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform. • GCP Professional Machine Learning Engineer certification is required. • Experience with version control systems such as Git. • Excellent problem-solving skills and attention to detail. • Strong communication and collaboration skills. Preferred Qualifications: • Master's degree or higher in Computer Science, Engineering, Mathematics, or a related field. • Experience with distributed computing frameworks such as Apache Spark. • Familiarity with containerization and orchestration technologies such as Docker and Kubernetes. • Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. • Experience with natural language processing (NLP) or computer vision (CV) techniques. • Experience with continuous integration and continuous deployment (CI/CD) pipelines. • Contributions to open-source projects or participation in relevant communities.