Verisign helps enable the security, stability, and resiliency of the internet. We are a trusted provider of internet infrastructure services for the networked world and deliver unmatched performance in domain name system (DNS) services.
We are a mission focused, values driven company where each individual can contribute to building a stronger, more secure internet. We offer a dynamic and flexible work environment with competitive benefits and the ability to grow your career.
Verisign is looking for an experienced Junior or Middle-level Java software engineer to expand the Name Studio API team ().
An ideal candidate should be fluent in Java, has knowledge of Machine Learning and/or LLMs, and be eager to learn as needed. In the candidate, we seek an understanding of software engineering fundamentals, including core Computer Science concepts, as well as hands-on problem-solving experience building software systems.
The candidate will be involved in all aspects of product development including ideation, design, implementation, deployment, and issue resolution. This will usually imply cross-team collaboration with Product, Engineering, Security and Operations.
Responsibilities include:
1. Develop 'Proof of concept' software applications based on research findings
2. Collaborate with internal and external stakeholders on software applications design, development and technology assessment
3. Work with stakeholders to define requirements specifications. Participates in requirements gathering, design, code and test plan reviews
4. Contribute to and drive future AI initiatives for the team
Requirements include:
5. Bachelors Degree in Computer Science, Information Systems, or related technical experience
6. 5+ years Software development experience
7. Advanced experience with Data Science, Machine Learning or Large Language Models
8. Experience with Java, Spring Boot, AWS Cloud, LLM Inference, MLOps
9. Masters Degree preferred
Product
Name Studio API () is an API-as-a-service recommender system for domain names. The following two videos explain briefly why our customers use the product: and
From the implementation standpoint, Name Studio API is a Java Spring Boot application implementing algorithms and using external libraries (such as Tensorflow) to generate domain suggestions. The system applies state-of-the-art neural language models and natural language processing algorithms on top multiple data sources, including trending topics, popular keywords, geography, semantic relevance, and others. This is done across 10+ languages (English, French, German, Spanish etc) and thousands of zones (.com, .net, .info, .ch, .fr, .de etc). Whenever you get a domain name suggestion online, be it with a blogging platform or a cloud provider, there is a high chance it is powered by our API behind the scenes.
The key challenges we face when building the product are obtaining high quality, relevant, and meaningful domain suggestions people like while offering very low response times on a global scale, serving high request volumes.
Team
Our team possesses complete engineering ownership over the product. The work style of the team is closer to an internal startup where all the team members are involved in the majority of product development phases and are flexible moving between focus areas.
In terms of the process, we rely on Scrum to structure our work, with tickets prioritized in Jira. Our code is located on internal GitHub; we follow Git Flow with pull request code reviews and extensive automation. For continuous delivery, we use Jenkins with pipelines and our product deployments are automated with Terraform and Ansible. The product can be rolled out to a cloud, from zero to the operating state in a single button click. We do builds for each codebase change as well as nightly builds. We have automated testing with substantial coverage. For processing large amounts of data, internal Hadoop and Spark clusters are available. Tensorflow and Keras enable us to go quickly from research prototypes trained on our GPU-powered servers to production-ready systems. On top of that, we leverage Large Language Models to generate creative suggestions.
While fluent in Java, it is beneficial if the candidate has experience working with some of the mentioned tools. Others can be learned as needed.