Job Description

Who We are

Oreyeon is a startup company providing AI solutions for airports focusing on safety and automation of operations. Oreyeon's goal is to re-imagine airport safety by implementing proactive features, eliminating human error, and reducing costs by using cutting-edge technologies.

What you’ll Bring

• Collaboration with team members
• Willingness to learn and grow
• Adaptability in a dynamic and fast-paced environment
• Fitting the inclusive and diverse work environment
• Recognizing and appreciating team effort
• Being mindful of inclusive language
• The ability to communicate your thoughts emphatically

We are looking for a Machine Learning Engineer Intern (MLOps) experienced in designing, implementing, and maintaining data/ML pipelines. You should be passionate about creating new technologies and building scalable end-to-end ML workflows.

Education: Bachelor's degree in Computer Science/ Software Engineering (similar technical field of study or equivalent practical experience)

Experience: 1+ years in the Machine Learning field or Applied Projects.

Responsibilities:

The responsibilities expected from the person filling the role include:

• Develop, optimize, and accelerate the ML lifecycle
• Maintain a scalable infrastructure through the use of MLOps tools to automate integrate and monitor operational processes along with our data platform
• Build and automate CI/ CD pipelines and QA systems to improve reliability, robustness, and speed
• Implement practices for monitoring, logging, and alerting on cloud environments
• Develop scalable data pipelines compatible with both the ML and production lifecycle (data flow, collection, annotation, processing, inference, and analytics)
• Develop set processes for data modeling and data production
• Identify ways to improve data reliability, efficiency, and quality
• Implement data visualization tools

Key Qualifications:

• Solid knowledge and proven experience in Python
• Solid understanding of machine learning principles and algorithms.
• Familiar with Amazon Web Services as a cloud service provider.
• Familiar with the machine learning lifecycle
• Basic understanding of software development practices, version control systems, and CI/CD pipelines.
• Solid knowledge of Data Structures and algorithms
• Familiar with database concepts (relational, non-relational, graph, etc.) and querying languages (SQL, NoSQL).
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
• Excellent communication and teamwork skills.

Preferred Qualifications:

• Experience with model implementation, monitoring, and deployment on AWS.
• Solid knowledge concerning data storage, data security, data privacy, and data modeling on a cloud platform.
• Experience with containerization technologies (e.g. Docker).
• Experience with building CI/CD pipelines. 

Other:

• This is a paid hybrid internship
• The internship will start during December

Company Profile