About the Role
As a Software Engineer, you will get a chance to choose from a myriad of projects: building signals and models for detecting bad users and rejecting fraudulent and abusive contributions, building tools that allow Google operators to efficiently provide labels for model training and the infrastructure on which all of these run. You will also use your programming skills, develop intuition for open ended problems and learn how Machine Learning can be applied to solve real world problems.
Responsibilities
- Design, develop, test, deploy, maintain and improve ML models/infrastructure and software that uses these models.
- Manage individual project priorities, deadlines and deliverables.
- Participate in cutting edge research in artificial intelligence and machine learning applications.
- Build the libraries and frameworks that support large, complex web applications.
- Contribute to engineering efforts from planning and organization to execution and delivery to solve complex, real world engineering problems.
Requirements
- Bachelor's degree in Computer Science, or related technical field, or equivalent work experience.
- 3 years of relevant work experience.
- Experience designing and implementing distributed software systems (e. g Java, C++, or Python).
- Research or Industry experience in Artificial Intelligence, Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Deep Learning.
Preferred qualifications
- Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning or related technical field.
- 2 years of relevant work experience in machine learning software development and architectures for machine learning (with focus on deep learning).
- Experience with one or more of the following areas: Server Backend Distributed and Parallel Systems, Full Stack Development (front end and backend), Scalable Enterprise Platforms and Applications, Application Security and Incident Management, Machine Learning, Information Retrieval or Natural language processing.
- Experience in building, deploying, and improving Machine Learning models and algorithms in real-world products.