Labelbox logo

Software Engineer, Early Professional

Labelbox

About The Role

As an early professional Software Engineer in the engineering organization at Labelbox, you will be responsible for developing features and capabilities for certain components within the different product areas. This includes platform, machine learning, and the product engineering teams. You will work closely with more experienced engineers, product managers, and designers to build and maintain a platform that enables our customers to build and deploy AI systems at scale.

Your Day to Day

  • Develop features and capabilities for large-scale systems within platform, machine learning, workflows, perception, editors, and other product areas.
  • Collaborate with team members and stakeholders.
  • Participate in sprint planning, standups, and other related activities.
  • Support 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.
  • Passionate about software engineering and building solutions for complex engineering problems.
  • Eager to learn and grow as an engineer while working on a high-impact product line in the AI domain.
  • Proficient in data structures and algorithms.
  • Fluent in programming languages such as TypeScript, Java, or Python.
  • 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

$105,000—$130,000 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.

Benefits
Extracted with AI

  • Hybrid work model
  • Collaboration and connection within tech hubs
  • Asynchronous communication
  • Autonomy and ownership of tasks

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