Python Machine Learning Engineer

Quadlight Corp Inc. is looking for a talented Python Machine Learning Engineer.

Location: Charlotte, NC

Job Type: Full-time

Number Of Openings: 1

Job Description:

As a Python Machine Learning Engineer, you will collaborate with data scientists and software engineers to design, develop, and deploy machine learning models and algorithms. You will play a crucial role in leveraging data to solve complex business problems and drive innovation using cutting-edge machine learning techniques.

• Design, develop, and implement machine learning algorithms and models using Python libraries such as Tensor Flow, PyTorch, or scikit-learn.
• Collaborate with data scientists and domain experts to understand business requirements and translate them into technical solutions.
• Preprocess and clean large datasets to prepare them for modeling and analysis.
• Perform exploratory data analysis (EDA) to uncover patterns and insights from data.
• Build and deploy scalable machine learning pipelines and workflows.
• Evaluate and benchmark model performance using appropriate metrics and techniques.
• Optimize machine learning models for performance, scalability, and efficiency.
• Implement data-driven solutions for real-time applications and systems integration.
• Stay updated with advancements in machine learning, artificial intelligence, and related fields.
• Document code, models, experiments, and findings in a clear and structured manner.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field. (Master’s degree preferred)
• Proven experience as a Machine Learning Engineer or in a similar role, with hands‑on experience in developing and deploying machine learning models.
• Proficiency in Python and its libraries for data manipulation, analysis, and modeling (e.g., pandas, numpy, scipy).
• Experience with machine learning frameworks and libraries such as Tensor Flow, PyTorch, scikit‑learn, etc.
• Strong understanding of machine learning algorithms, statistics, and data science concepts.
• Knowledge of software engineering best practices, including version control (e.g., Git) and testing methodologies.
• Excellent problem‑solving skills and ability to work independently or in a team environment.
• Strong communication skills and ability to collaborate effectively with cross‑functional teams.

• Experience with cloud platforms and services for machine learning deployment (e.g., AWS Sage Maker, Google AI Platform).
• Familiarity with big data technologies (e.g., Hadoop, Spark) and distributed computing.
• Previous experience in deploying machine learning models into production environments.
• Contributions to open-source machine learning projects or publications in relevant conferences/journals.