Python Machine Learning Engineer

Quadlight Corp.; Charlotte (NC); On-site; USD 110,000 - 160,000; Full time

Job summary

Quadlight Corp Inc. in Charlotte, NC is seeking a talented Python Machine Learning Engineer to design, develop, and deploy ML models and algorithms.

You will collaborate with data scientists and software engineers to translate business requirements into scalable solutions, build ML pipelines, and stay updated on ML advances.

Qualifications

• Bachelor's degree in CS, engineering, mathematics, or related field.
• Hands-on experience building and deploying ML models.
• Strong Python and data manipulation libraries (pandas, numpy, scipy).
• Experience with ML frameworks such as TensorFlow, PyTorch, scikit-learn.
• Solid understanding of ML algorithms, statistics, and data science concepts.
• Familiarity with software engineering best practices, version control, and testing.
• Excellent problem-solving and communication skills for cross-functional teams.

Responsibilities

• Design, develop, and deploy ML models and algorithms.
• Collaborate with data scientists and software engineers to translate requirements.
• Preprocess and clean large datasets for modeling.
• Perform exploratory data analysis to derive insights.
• Build scalable ML pipelines and workflows.
• Evaluate models using appropriate metrics and benchmarks.
• Document experiments and results clearly.

Skills

Python programming

Data preprocessing

EDA

Model evaluation

Deployment pipelines

Cloud platforms knowledge

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field

Master's degree preferred

Tools

TensorFlow

PyTorch

scikit-learn

pandas

numpy

scipy

AWS SageMaker

Google AI Platform

Job description

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

Company: Quadlight Corp Inc.

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 TensorFlow, 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 TensorFlow, 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 SageMaker, 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.