AI/ML Engineer

Job Title: AI/ML Engineer

Job Type: Contractor

Location: Remote

Job Summary:

Join our customer's team as an AI/ML Engineer, where you will leverage your expertise in machine learning, Python, and ETL to drive impactful data solutions. This expert-level remote position offers the opportunity to collaborate with a talented group of professionals and make a significant impact by building robust, scalable AI systems.

Key Responsibilities:

• Design, develop, and deploy machine learning models to solve complex business challenges.
• Collaborate with cross-functional teams to understand requirements, define data pipelines, and deliver high-impact AI solutions.
• Implement, optimize, and maintain ETL processes for efficient data ingestion, transformation, and management.
• Utilize Python and relevant libraries to develop clean, efficient, and reusable code for AI and machine learning applications.
• Continuously monitor, evaluate, and improve the performance and accuracy of deployed models.
• Communicate technical concepts clearly and effectively with both technical and non-technical stakeholders.
• Document processes, methodologies, and model decisions to ensure transparency and reproducibility.

Required Skills and Qualifications:

• Expert-level proficiency in machine learning techniques and algorithms.
• Advanced programming skills in Python and its data science ecosystem (NumPy, pandas, scikit-learn, etc.).
• Hands-on experience designing and managing ETL workflows in production environments.
• Strong understanding of data preprocessing, feature engineering, and model evaluation metrics.
• Excellent written and verbal communication skills; ability to convey complex ideas succinctly.
• Proven ability to collaborate and thrive in remote, distributed team settings.
• Track record of delivering robust, scalable machine learning solutions in real-world contexts.

Preferred Qualifications:

• Experience working with cloud platforms for AI/ML such as AWS, GCP, or Azure.
• Background in deploying models in production environments (e.g., using Docker, Kubernetes, or MLflow).
• Advanced degree in Computer Science, Data Science, or a related field.