Title:

Machine Learning Engineer – Python

Job Description
We are seeking a Machine Learning Engineer with strong Python expertise to support the development, deployment, and optimization of machine learning models in a production environment. This role requires a blend of software engineering, data pipeline development, and model integration to drive data-driven decision-making.

Key Responsibilities

Machine Learning Model Development & Integration

• Develop, optimize, and implement machine learning algorithms for real-world applications.
• Design and deploy scalable data pipelines to support machine learning workflows.
• Ensure seamless integration of ML models into production environments, adhering to SDLC best practices for model deployment and lifecycle management.

Data Engineering & Pipeline Development

• Build and maintain data pipelines using Python, PySpark, and cloud-based technologies (AWS, Glue, SageMaker, etc.).
• Analyze raw data sources for quality, consistency, and usability in model development.
• Support automated data ingestion and transformation to enhance model performance.

Model Monitoring & Performance Optimization

• Implement automated monitoring scripts to track model performance and alert management to potential issues.
• Troubleshoot and refine machine learning pipelines to maintain accuracy and efficiency over time.
• Collaborate with data scientists and engineers to review and improve model architectures.

Business & Cross-Functional Collaboration

• Engage with internal stakeholders to understand business challenges and translate them into ML-driven solutions.
• Participate in business planning and prioritization to align machine learning initiatives with company goals.
• Document and communicate design changes to data science teams and leadership.

Qualifications & Skills

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience).
• 5+ years of experience in machine learning engineering or a related field.
• Proficiency in Python, PySpark, and SQL for data manipulation and model development.
• Experience with NoSQL databases and data storage solutions.
• Hands-on experience with AWS cloud technologies (Glue, SageMaker, Lambda, etc.).
• Strong understanding of distributed computing and big data processing.
• Ability to troubleshoot, debug, and optimize ML models and data pipelines in production.

Preferred Qualifications

• Experience with MLOps practices for automated model deployment and management.
• Knowledge of containerization (Docker, Kubernetes) for scalable model deployment.
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
• Understanding of data governance, compliance, and security in machine learning applications.

 

About Us:

SourceAbility provides best-in-class recruitment services primarily in the areas of Data & Analytics. We strive to work with client companies that provide exceptional work environments for the candidates we represent. Our staff is highly trained in multiple verticals and works to ensure a positive experience when working with a recruitment firm. SourceAbility, Inc. does not discriminate in the acceptance or referral of candidates on the basis of race, color, religion, sex, age, national origin, marital status, disability, or other protected characteristics.

Contact
Please contact Tanya Calkins at SourceAbility. 704-837-8202: tanya@sourceabilityinc.com

Posted On: Tuesday, March 18, 2025