Machine Learning Engineer => Relocate to China
Full-time
MS Systems
Job Description:
Position: Machine Learning Engineer Location: Remote / Hybrid
Employment Type: Full-time Responsibilities Design, train, and deploy machine learning models for production environments. Build data pipelines for model training, evaluation, and optimization. Work with large-scale datasets, perform feature engineering, data cleaning, and model tuning. Develop scalable algorithms for NLP, computer vision, or recommendation systems. Collaborate with product and engineering teams to integrate ML solutions. Monitor model performance and ensure reliability, accuracy, and efficiency. Document ML workflows, research findings, and technical guidelines. Requirements:
Requirements Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related discipline. Strong foundation in machine learning, statistics, and applied mathematics. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/K8s). Knowledge of MLOps best practices is a strong plus. Excellent problem-solving and analytical skills.
Benefits: Skills:
Ability To Work Under Pressure, Big Picture Thinking, Electro-Mechanical Products
Position: Machine Learning Engineer Location: Remote / Hybrid
Employment Type: Full-time Responsibilities Design, train, and deploy machine learning models for production environments. Build data pipelines for model training, evaluation, and optimization. Work with large-scale datasets, perform feature engineering, data cleaning, and model tuning. Develop scalable algorithms for NLP, computer vision, or recommendation systems. Collaborate with product and engineering teams to integrate ML solutions. Monitor model performance and ensure reliability, accuracy, and efficiency. Document ML workflows, research findings, and technical guidelines. Requirements:
Requirements Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related discipline. Strong foundation in machine learning, statistics, and applied mathematics. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/K8s). Knowledge of MLOps best practices is a strong plus. Excellent problem-solving and analytical skills.
Benefits: Skills:
Ability To Work Under Pressure, Big Picture Thinking, Electro-Mechanical Products
Vacancy posted 3 days ago
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