Note: The job is a remote job and is open to candidates in USA. CareerXperts Consulting is seeking a Machine Learning Engineer to advance its business through artificial intelligence and machine learning. The role manages the full machine learning lifecycle, including data preparation, model development, production integration, monitoring, optimization, and documentation while collaborating across the organization.

Responsibilities

• Collaborate with data scientists, business analysts, and product managers to understand business problems and translate them into machine learning solutions
• Acquire, clean, and pre-process large datasets for machine learning model training
• Develop, train, and evaluate machine learning models using various algorithms (e.g., supervised learning, unsupervised learning, deep learning)
• Experiment with different model architectures and hyperparameter tuning to optimize model performance
• Integrate machine learning models into production systems and applications
• Monitor and maintain deployed models, ensuring accuracy, efficiency, and fairness
• Analyze model performance metrics and identify opportunities for improvement
• Stay up-to-date with the latest advancements in machine learning research and best practices
• Document your work clearly and concisely for future reference
• Collaborate with colleagues across the organization to foster a data-driven culture

Skills

• Master's degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience)
• Minimum of 3+ years of experience in machine learning engineering or a related field
• Strong understanding of machine learning concepts, algorithms, and frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
• Proficiency in programming languages commonly used in machine learning (e.g., Python, R)
• Experience with data wrangling, cleaning, and manipulation techniques
• Excellent analytical and problem-solving skills
• Strong communication, collaboration, and interpersonal skills
• Ability to work independently and take ownership of projects
• Experience with cloud platforms for machine learning (e.g., AWS SageMaker, Azure Machine Learning) is a plus

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