Appier is hiring a
Software Engineer, Machine Learning

Summary

The Machine Learning Engineer Intern will collaborate with senior engineers and data scientists to design and implement experiments to improve machine learning models' performance, assist in deploying machine learning models into production environments using CI/CD pipelines, set up monitoring and logging for ML models, work on data pipeline automation, ensure data quality throughout the ML pipeline, maintain clear documentation of all processes, tools, and models deployed, contribute to the automation of repetitive tasks related to model training, testing, and deployment, help manage and optimize ML infrastructure on cloud platforms (e.g., AWS, GCP, Azure) for scalability and performance, and have strong programming skills in languages such as Python/Golang.

Requirements

• Currently enrolled in an undergraduate or graduate program (Bachelor's, Master's, or Ph.D.) in computer science, artificial intelligence, machine learning, or a related field
• Strong programming skills in languages such as Python/Golang
• Basic understanding of large language model (LLM) concepts and experience with LLM providers like OpenAI, Anthropic, and Mistral AI
• Basic understanding of DevOps practices and tools such as Docker and Kubernetes
• Excellent problem-solving skills and analytical thinking
• Ability to work independently as well as collaboratively in a team environment
• Good communication skills with the ability to present complex ideas effectively

Responsibilities

• Collaborate with senior engineers and data scientists to design and implement experiments to improve machine learning models' performance
• Participate in team meetings, contributing ideas to drive innovation in machine learning projects
• Assist in deploying machine learning models into production environments using CI/CD pipelines
• Set up monitoring and logging for ML models to ensure reliability, and build dashboards to ensure performance in production
• Work on data pipeline automation, and ensuring data quality throughout the ML pipeline
• Maintain clear and concise documentation of all processes, tools, and models deployed
• Contribute to the automation of repetitive tasks related to model training, testing, and deployment
• Help manage and optimize ML infrastructure on cloud platforms (e.g., AWS, GCP, Azure) for scalability and performance

Preferred Qualifications

• Previous experience or coursework in large language model (LLM) or machine learning
• Familiarity with deep learning frameworks and libraries
• Experience with large-scale data processing and distributed computing platforms
• Demonstrated interest in advancing machine learning techniques and applications
• Experience in building and deploying automation and continuous integration systems
• Experience in operating services on IaaS such as AWS and GCP