Junior 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 motivated and technically skilled Junior Machine Learning Engineer (MLE) to join our innovative Research & Development team. This entry-level position is ideal for a recent graduate or early-career professional passionate about building and deploying robust, scalable machine learning systems. You can apply your software engineering skills to operationalize machine learning models, contributing to the infrastructure, tools, and processes that power our AI-driven products. Working closely with experienced MLEs, data scientists, and software engineers, you will play a key role in bridging the gap between model development and real-world application.

Responsibilities

• Assist in developing, implementing, and maintaining machine learning pipelines for model training, evaluation, deployment, and monitoring.
• Integrate machine learning models into production applications and services, ensuring reliability and performance.
• Contribute to developing MLOps tools and infrastructure for model versioning, management, and automation.
• Help optimize machine learning models and inference pipelines for speed, scalability, and resource efficiency.
• Implement testing strategies and quality assurance measures for ML systems.
• Troubleshoot and resolve issues related to the deployment and operation of machine learning models.
• Apply software engineering best practices (e.g., version control with Git, code reviews, unit/integration testing, CI/CD) to ML projects.
• Create and maintain clear documentation for ML system designs, deployment procedures, and operational playbooks.
• Actively participate in team meetings and technical discussions, and contribute to a culture of continuous improvement and innovation.

Required Skills

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science (with a strong engineering/CS focus), or a closely related technical field.
• Solid foundation in software engineering principles, including data structures, algorithms, object-oriented design, and system design.
• Proficiency in Python for software development, scripting, and machine learning applications.
• Understanding core machine learning concepts, standard algorithms, and the model development lifecycle.
• Experience with version control systems, notably Git.
• Strong analytical and problem-solving skills, with an ability to debug complex systems.
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
• A proactive and enthusiastic approach to learning new technologies and engineering practices in the ML domain.

Bonus Skills

• Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with Linux/Unix environments, shell scripting, and command-line tools.
• Exposure to containerization technologies (e.g., Docker) and orchestration (e.g., Kubernetes).
• Basic understanding of cloud computing platforms (e.g., AWS, Azure, GCP) and their ML/AI services.
• Knowledge of CI/CD pipelines and tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Familiarity with MLOps concepts, tools (e.g., MLflow, Kubeflow), and best practices.
• Experience with API development and integration (e.g., REST, gRPC).
• Knowledge of C++ for performance-critical components in ML systems.
• Basic understanding of CUDA programming and GPU architecture for accelerating ML workloads.
• Previous internship experience in machine learning engineering, software engineering, or a related role.

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!