Quid is searching for a talented and passionate Machine Learning Engineer Intern to join the Artificial Intelligence R&D team! The mission of the AI R&D team is to drive innovation in Data Science, Natural Language Processing, and Computer Vision to surface insights from massive amounts of social media, survey data, news and industry database. We are delivering on the promise of AI-assisted analytics, earning a position as a leader in our space in a 2020 Forrester Wave report.
In this Machine Learning Engineer Intern role, you will work closely with AI R&D team to tackle problems in content discovery, text mining and data analytics, with projects such as:
- Discovering topics of conversation across billions of social media posts
- Identifying and tracking trends
- Enabling user-driven customizations, e.g. with transfer learning
- Correlating natural language data with business metrics
- Building knowledge graph to help customer discover insights
Quid is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Responsibilities
- You are expected to work with our AI engineers to apply scientific thinking and techniques to implement experimental product features
- You will be coding in Python/Java, working on Hadoop/Spark and Kubernetes
- You will build machine learning models through all phases of development, from design through training, evaluation, and implementation in AI system.
- You will be presenting result of experiment to team and product manager
- You will work with team to apply CI/CD in project development
Requirements
- At least 6 months commitment, available to work 24 hours per week, and 40 hours per week during summer vacation (WFH is fine).
- Currently pursuing or holding a Bachelor's, Master's, or Ph.D. degree in Computer Science or a related field.
- Experience with statistical modeling, machine learning techniques applied to natural language processing
- Practical experience in training model and developing machine learning system
- Good communication and collaboration skills to work with people, passionate to solve challenging problems.
Nice To Haves
- Understanding of deep learning algorithms and workflows
- Familiarity with technologies like Tensorflow, SparkMLlib, and Scikit-learn
- Experience with social media data
- Utilizing LLM or grasping some of the LLM principles.
