Sr Engineer - Interactive Compute
Role details
Job location
Tech stack
Job description
As a Senior Engineer on the Machine Learning Platform team, you will develop new capabilities to support Data Scientists and other users at Target. You will gain insights into application architecture, distill abstract concepts into concrete designs, and influence implementation. Your expertise in software engineering patterns will help build robust and scalable systems. You will apply your programming skills to develop the product and influence your fellow engineers through proposing software designs and providing feedback. Your problem-solving skills will assist the team in triaging operational issues and eliminating repeat occurrences., * Lead the design, implementation, and maintenance of Interactive Compute platform capabilities.
- Develop applications to improve development experiences for Engineers, Data Scientists, and Analysts using JupyterLab and similar technologies
- Collaborate closely with our team and users to enhance notebook and Interactive Compute features for Target.
Additional R esponsibilities:
Develop, deploy, and maintain production applications.
- Build and maintain scalable, reliable, and efficient Compute capabilities.
- Implement monitoring and logging tools to ensure optimal system performance.
- Continuously improve platform performance, scalability, and reliability.
- Create and maintain technical documentation for users.
- Stay updated on the latest MLOps and cloud computing technologies.
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
Requirements
- Bachelor's degree or equivalent experience.
- 5+ years of software development experience.
- Proficiency in Java, Python, or similar languages.
- Experience with JupyterLab or Notebooks
- Experience in API development.
- Familiarity with relational databases and NoSQL technologies.
- Experience with Spark and Hadoop technologies.
- Preferred experience with Spring Boot
- Preferred experience with MLOps and machine learning concepts
- Familiarity with DevOps practices and tools such as Kubernetes, Docker, Jenkins, and Git.
- Strong analytical and problem-solving skills.