Full-Time

Senior Backend Engineer

Confirmed live in the last 24 hours

DataRobot

DataRobot

501-1,000 employees

AI platform for data analysis and processing

Data & Analytics
AI & Machine Learning

Senior, Expert

Boston, MA, USA + 2 more

More locations: Seattle, WA, USA | San Francisco, CA, USA

Category
Backend Engineering
Software Engineering
Required Skills
Kubernetes
Microsoft Azure
Python
Data Science
Data Structures & Algorithms
AWS
Go
Google Cloud Platform
Requirements
  • 3 years up to 10+ years of proven experience writing high-quality code in a collaborative environment preferably using Python and/or Go
  • Strong Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem-solving, and complexity analysis.
  • An understanding of design for scalability, performance, and reliability.
  • Deep experience with automated testing and test-driven development
  • Demonstrable knowledge of software architecture for large systems
  • Real-world experience decoupling monolithic software into smaller reusable components
  • Self-motivated and proactive, able to take ownership and deliver results.
  • Ability and willingness to learn about new technologies.
  • Personal drive to get things finished.
  • Effective communication behavior.
  • Fundamental understanding of Kubernetes and Helm. Experience in building and running software systems on Kubernetes clusters in production
  • Hands-on experience with infrastructure provisioning and configuration using Infrastructure as Code (IaC) principles
  • Experience with AWS, Azure, and/or Google Cloud platforms
  • CKAD (Certified Kubernetes Application Developer) certification
  • Publicly reviewable contributions to interesting development projects.
  • Experience supporting user-facing code and APIs.
  • Data Science experience
  • Identity and Access Management experience
  • CI/CD pipeline experience
Responsibilities
  • Develop, test, and support features of DataRobot.
  • Create and maintain automated unit tests and functional tests.
  • Design infrastructure for new features with the input of peers.
  • Manage individual projects and milestones with abundant communication of progress.
  • Seek, give, and receive critical feedback in a constructive manner, including but not limited to code reviews.
  • Engage in engineering on-call escalated support of services owned by the team.
  • Competencies should be at a level where a manager can have high confidence in an engineer’s ability to deliver complex solutions on time on an agreed-upon roadmap and manage technical risks.
  • Should be capable of working with product management to get requirements and drive technical feedback on complexity/approaches.

DataRobot provides an artificial intelligence platform that simplifies and enhances data analysis and processing for various industries. The platform integrates data from multiple sources, applies Extract, Transform, Load (ETL) processes, and utilizes AI tools to help clients improve their operations and decision-making. For example, companies like FordDirect and OYAK Cement have used DataRobot to better understand their customers and optimize their processes, respectively. Unlike many competitors, DataRobot focuses on unifying these elements into a single platform, making it easier for clients to leverage data effectively. The company's goal is to empower organizations to make informed, data-driven decisions that lead to improved performance and efficiency.

Company Stage

N/A

Total Funding

$1B

Headquarters

Boston, Massachusetts

Founded

2012

Growth & Insights
Headcount

6 month growth

-3%

1 year growth

-4%

2 year growth

-14%
Simplify Jobs

Simplify's Take

What believers are saying

  • DataRobot's collaborations, such as with IMDA for Project Moonshot, expand accessibility and usability of AI tools, fostering innovation.
  • The launch of groundbreaking tools like AI Observability with real-time intervention for Generative AI highlights DataRobot's commitment to cutting-edge technology.
  • Being named a leader in the Gartner Magic Quadrant enhances the company's reputation, potentially attracting more clients and top talent.

What critics are saying

  • The competitive AI and data analytics market requires continuous innovation to maintain leadership, posing a risk if DataRobot fails to keep pace.
  • Integration challenges with partners like Teradata could lead to technical issues or delays, impacting client satisfaction.

What makes DataRobot unique

  • DataRobot's integration of ETL processes with AI tools offers a unified platform that simplifies data handling and analysis, unlike competitors who may offer these services separately.
  • The company's focus on advanced LLM evaluation and assessment metrics provides unique capabilities that set it apart from other AI platforms.
  • Recognition as a leader in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms underscores its industry leadership and credibility.

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