Senior Backend Engineer, Orchestration: Distributed Systems

Posted 10 Days Ago
Be an Early Applicant
7 Locations
190K-225K Annually
Senior level
Artificial Intelligence • Information Technology • Machine Learning
Our mission is to build the best products to align with artificial intelligence.
The Role
As a Senior Backend Engineer, you will develop features for orchestration of large-scale workflows, working with distributed queues, databases, and message brokers. You will collaborate cross-functionally, mentor junior engineers, and participate in planning and documentation efforts.
Summary Generated by Built In

Labelbox is the data factory for generative AI, providing the highest quality training data for frontier and task-specific models. Labelbox’s comprehensive platform combines on-demand labeling services with the industry-leading data labeling platform. The Boost labeling service is powered by the Alignerr community of highly-educated experts, who span all major languages and a diverse range of advanced subjects. They are available on-demand to rapidly generate new data for supervised fine-tuning, RLHF, and more. Labelbox’s software-first approach delivers unmatched control and transparency into the labeling process, leading to the generation of high-quality, consistent data at scale.

Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs.


About the Role

As a Senior Backend Software Engineer on the Orchestration engineering team at Labelbox, you will work on the critical distributed software architecture that drives our offerings for data labeling. You will develop features for orchestration of large-scale workflows using distributed queues, databases, message brokers and job management mechanisms. You will get to own specific components of this area, and work end-to-end on projects from design to delivery. You will use your experience and expertise to collaborate cross-functionally with Product, Design and other stakeholders to transform ideas into shipped features and capabilities to drive scale and adoption of our offerings, as well as enable our customers to be successful.

Your Day to Day

  • Develop features and capabilities for orchestration of large-scale workflows using distributed queues, databases, message brokers and job management mechanisms.
  • Collaborate with team members and stakeholders.
  • Participate in sprint planning, standups and other related activities.
  • Mentor and guide less experienced engineers while driving initiatives towards completion.
  • Particulate in supporting the team’s area of ownership by working with the Support organization to help resolve any customer issues.
  • Stay abreast of industry trends and emerging technologies. Analyze, assess and incorporate relevant technologies and ideas as needed.
  • Contribute to technical documentation, research publications, blog posts, and presentations at conferences and forums.

About You

  • Bachelor’s degree in computer science or related field. Advanced degree preferred.
  • 5+ years of work experience in a software company in backend software engineering, specifically in distributed systems.
  • Extensive software design and architecture skills in large-scale systems, including previous projects in this area.
  • Strong grasp of databases, queues, job management, message brokers, in-memory caching, etc.
  • Previous experience working with APIs using REST and GraphQL.
  • Knowledge of using NodeJS for backend development. Experience with NestJS is preferred.
  • Good understanding of memory management and related optimizations in large-scale systems.
  • Good understanding of, or interest in, the overall Data + AI ecosystem and how it pertains to design and architecture of large-scale AI platforms.
  • Experience with container orchestration systems such as Kubernetes.
  • Proficient in data structures and algorithms.
  • Fluent in programming languages such as Typescript, Java, or Python.
  • Demonstrated ability to keep up with industry trends and new developments.
  • Excellent communication and collaboration skills.
  • Strong sense of ownership.
  • Thrive in a fast-paced environment with willingness and ability to dive deep.
  • Comfortable with ambiguity and able to break-down high level requirements into actionable tasks in a methodical manner.
  • Resourceful and creative problem-solver with an attention to detail who will not hesitate to take initiative and get things done.

Engineering at Labelbox

We build a comprehensive platform and end-to-end tool suite for AI system development. We believe in providing the best user experience at scale with high quality. Our customers use our platform in production environments, daily, to build and deploy AI systems that have a real positive impact in the world. 

We believe in collaborative excellence and shared responsibility with decision making autonomy wherever possible. We strive for a great developer experience with continuous fine tuning. How we work is one of the cornerstones of engineering excellence at Labelbox.

We learn by pushing boundaries, engaging in open debate to come up with creative solutions, then committing to execution. We continuously explore and exploit new technologies, creating new and perfecting existing techniques and solutions. Making customers win is our North Star.

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.

Annual base salary range

$190,000$225,000 USD

Excel in a remote-friendly hybrid model.

We are dedicated to achieving excellence and recognize the importance of bringing our talented team together. While we continue to embrace remote work, we have transitioned to a hybrid model with a focus on nurturing collaboration and connection within our dedicated tech hubs in the San Francisco Bay Area, New York City Metro Area, and Wrocław, Poland. We encourage asynchronous communication, autonomy, and ownership of tasks, with the added convenience of hub-based gatherings.

Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.

Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

Top Skills

Nestjs
Node.js
The Company
HQ: San Francisco, CA
115 Employees
Hybrid Workplace
Year Founded: 2017

What We Do

Labelbox is the data factory for generative AI, providing the highest quality training data for frontier and task-specific models. Labelbox’s comprehensive platform combines on-demand labeling services with the industry-leading data labeling platform. The Boost labeling service is powered by the Alignerr community of highly-educated experts, who span all major languages and a diverse range of advanced subjects. They are available on-demand to rapidly generate new data for supervised fine-tuning, RLHF, and more. Labelbox’s software-first approach delivers unmatched control and transparency into the labeling process, leading to the generation of high-quality, consistent data at scale. Customers include Fortune 500 enterprises and leading AI labs, and Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins.

Why Work With Us

Labelboxers are driven to master their craft and build the best products for AI, which is quickly becoming one of the most significant technologies of our time. Join us in supporting our customers as they create AI breakthroughs.

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