Job Details

Location: San Francisco, USA
Schedule: full time

What is a Stack?

The stack is the set of technologies needed to make an end-to-end product or solution.

What is a Full Stack Engineer?

A full stack engineer works with both the front end–the user end–and the back end–or database side– of a website or application. They tackle projects including user-facing websites, databases, applications and work on projects from planning through delivery.

What are the responsibilities of a Full Stack Engineer?

As a full stack engineer at Happy Elements, you will:

• Design and build the data science platform that enables data scientists and machine learning engineers with the ability to build, train, validate and deploy machine learning (ML) models quickly;
• Build components to support machine learning modeling and build data integration and data preprocessing pipelines from tens of data sources for use in data science and machines learning models;
• Leverage modern tools and frameworks to improve the performance of data science services and optimize the workflow efficiency and quality of modeling;
• Participate in and contribute to the full project lifecycle system design, implementation, testing, and deployment;
• Follow standard software development methodologies and SDLC practices to efficiently produce high quality applications;
• Participate in estimating assigned work effort and be accountable for completion dates;
• Document code so other engineers can reuse and support components in the future;
• Improve the performance and scalability of data science services.

To be eligible for consideration at Happy Elements, your qualifications must include:

• MS in Computer Science, Statistics, Engineering or other relevant field with equivalent technical experience;
• 2+ years of experience working in a software engineering-related role;
• A curious mind and the ability to translate complex requirements and technical challenges into solid implementations;
• Strong object-oriented programming and design skills in Python or Java;
• Hands-on experience with big-data technologies such as SQL, Hive, Hadoop and Spark;
• Experience with–or a strong desire to learn–statistical modeling and machine learning techniques;
• Excellent communication skills with meticulous attention to detail;
• Experience in data science packages and tools is a plus.