Intern Machine Learning Engineer

About Qwerky AI

QWERKY AI is a human-centered artificial intelligence company focused on building practical and approachable AI tools for real-world use. Headquartered in Columbia, South Carolina, with a distributed team across the U.S., QWERKY is led by a founding team of tech entrepreneurs with over a decade of experience. The company is dedicated to creating AI that enhances — rather than replaces — human intelligence. QWERKY AI is currently developing an AI platform to empower knowledge workers, creatives and small businesses.

Job Description

QWERKY AI seeks a bright and motivated Machine Learning Engineer (MLE) Intern to join our innovative Research & Development team. This internship provides a fantastic opportunity to gain hands-on experience in the operational aspects of machine learning, bridging the gap between model development and production deployment. The ideal candidate is passionate about building robust and scalable ML systems, has a foundational understanding of software engineering principles, and is eager to learn about MLOps practices. You will work closely with our experienced MLEs, data scientists, and software engineers, contributing to the infrastructure, tools, and processes that bring our AI models to life.

Responsibilities

• Assist in developing and maintaining machine learning pipelines for training, evaluation, and deployment.
• Support the integration of machine learning models into existing applications and services.
• Contribute to developing tools and infrastructure for model monitoring, versioning, and management (MLOps).
• Help optimize machine learning models for performance, scalability, and resource efficiency in production environments.
• Collaborate on testing and quality assurance for ML systems.
• Assist in troubleshooting and resolving issues related to deployed machine learning models.
• Learn and apply software engineering best practices (e.g., version control, code reviews, testing) in the context of ML systems.
• Document ML system designs, deployment processes, and operational procedures.
• Participate in team meetings and technical discussions, and contribute to a collaborative engineering culture.

Required Skills

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science (with a strong engineering focus), or a related technical field.
• Solid understanding of fundamental software engineering concepts (e.g., data structures, algorithms, object-oriented programming).
• Proficiency in Python for software development and scripting.
• Basic understanding of machine learning concepts and workflows.
• Familiarity with version control systems, notably Git.
• Strong problem-solving and analytical skills.
• Good communication and collaboration skills.
• A proactive attitude and eagerness to learn new technologies and engineering practices.

Bonus Skills

• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with Linux/Unix environments and shell scripting.
• Exposure to containerization technologies like Docker.
• Basic understanding of cloud computing platforms (e.g., AWS, Azure, GCP).
• Knowledge of CI/CD (Continuous Integration/Continuous Deployment) principles.
• Familiarity with MLOps concepts and tools.
• Experience with API development (e.g., REST, gRPC).
• Knowledge of C++ for performance-sensitive components.
• Basic understanding of CUDA and GPU architecture.

Pay / Benefits

• Salary or hourly rate
• Stock options plan (we are a private company, so this is not liquid) 
• If you are in the USA: healthcare, dental, vision, 401k 
• Unlimited time off policy
• Flexible working hours

Hiring Process

• Submit a resume to us for review.
• We will follow up with a technical screening (this will take approximately one hour).
• Following the successful completion of the technical screening, we will schedule an Onsite Interview.
• The Onsite Interview to meet more of the team, it will consist of the following (total time three hours):
• • Technical Screenings (1-2)
  • System Design
  • Behavioral Interview
• We’ll reach out with an offer if you're a great fit. 
• Once accepted, you start working with us!