Full Stack Software Engineer (Ruby)

Posted 8 Days Ago
Be an Early Applicant
Arlington, VA
Hybrid
5-7 Years Experience
Artificial Intelligence
The Role
As a Full Stack Software Engineer, you will be responsible for deploying and maintaining a microservice architecture to multiple cloud providers, working with cloud services, debugging problems in Kubernetes/Docker, and debugging code across multiple languages and technologies.
Summary Generated by Built In

Artificial Intelligence (AI) is transforming government. Across Defense, Health and Human Services, Homeland Security and Emergency Management, Sciences, Natural Resources and Regulatory functions- all are recognizing the power of human-machine teaming. Nothing moves in AI and machine learning (ML) without training data, and only high-quality training data can produce accurate and robust AI/ML powered solutions. Creating high quality training data at the scale necessary to meet the demands of our government mission partners is incredibly challenging. Few companies can do it. Even fewer can do it well. Since 2017, Figure Eight Federal has proven it can do both.


In March 2019, Figure Eight was acquired by Appen. Headquartered in the National Capital Region, Figure Eight Federal was created to specifically serve the needs of our government customers. Together, Appen and Figure Eight Federal, combine the best of human and machine intelligence to provide high-quality annotated training data that powers the world’s most innovative machine learning (ML) mission solutions. The Figure Eight platform enables ML and data-driven business solutions to scale across a diverse set of industries including retail, automotive, finance, manufacturing, agriculture, life sciences, robotics, and more. The Figure Eight platform transforms audio, video, text, and images into high-quality annotated data to support a variety of use cases ranging from computer vision and search relevance to data categorization and natural language processing (NLP). Learn more at www.f8-federal.com.


As a member of our team, you will be building annotation tools marking up text, audio, images, video and other datatypes for use in creating machine learning models. You will provide the amazing experiences for the users, fixing bugs as necessary and constantly working on improving the quality of our codebase.

Responsibilities

  • Deploy and maintain our microservice architecture to multiple cloud providers
  • Work with cloud services such as EKS, S3, RDS, Lambda, etc.
  • Debug problems in Kubernetes/Docker
  • Debug problems in code across multiple languages (Ruby, JavaScript, Java, Python) and technologies

Qualifications:

  • 2+ years' experience with Kubernetes and Docker
  • 4+ years' experience with common programming languages (Ruby, JavaScript, Java, Python)
  • 2+ years' experience with cloud technologies (AWS, Azure, GCE)
  • 2+ years' experience with relational databases
  • Experience with networking fundamentals and troubleshooting connections
  • Comfortable with Linux and shell scripting
  • Assertive "get things done" attitude
  • Excellent communication skills (written and verbal)
  • Ability to come into the office 1-3 times per week, as needed
  • Willingness to go through a security clearance process

Preferred Qualifications:

  • Active clearance
  • Master's degree in computer science

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Top Skills

Docker
Java
JavaScript
Kubernetes
Python
Ruby
The Company
Arlington, VA
13 Employees
On-site Workplace
Year Founded: 2007

What We Do

Figure Eight Federal is critical in the creation of the highest quality Decision-Grade AI for leaders engaged in advancing America's security and competitive position. With a deep expertise and ability to train all data types, Figure Eight Federal works with sectors including defense, health, finance, agriculture, and science to fuel and accelerate Federal AI initiatives, and explicate the most value from data.

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