Forward Deployed Engineer, Robotics

Shape the Future of AI

At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.

About Labelbox

We're the only company offering three integrated solutions for frontier AI development:

1. Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale
2. Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models
3. Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling

Why Join Us

• High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.
• Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.
• Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.
• Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.
• Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.

Role Overview

Get an inside look and hear directly from our current Forward Deployed Engineers here

We are hiring a Robotics Data Pipeline & QA Engineer to build end-to-end infrastructures that move robotics video, sensor data, annotation output, and review results reliably through labeling workflows. You will combine software engineering, data pipeline design, robotics context, and automation-driven QA systems to ensure the highest-quality data is produced at scale.

Your work ensures robotics teams can collect, label, and validate thousands of hours of data per week with confidence and cost-efficiency.

Your Impact

• Build and optimize ingestion pipelines for robotics video, synchronized metadata, sensor logs, and derived annotations.
• Architect scalable labeling workflows that maintain ID integrity, time alignment, and version control across large datasets.
• Implement automated QA flows using heuristics, statistics, and LLM-based validation to reduce manual QA burden.
• Create dynamic trust scoring systems that ramp-down review percentage as contributors prove consistent quality.
• Track data progression across ingestion → labeling → review → acceptance → downstream consumption.
• Build monitoring systems for throughput, failure rates, accuracy, contributor performance, and cost impact.
• Identify robotic-specific annotation edge cases and translate them into codified criteria and QA logic.
• Collaborate with internal Platform, Infra, and ML teams to integrate tooling end-to-end.

You're a Fit If You:

• Have hands-on experience with robotics systems, perception stacks, simulation, or structured robotics datasets.
• Can translate robotics data failure modes into measurable quality gates.
• Understand tradeoffs between human-in-loop QA vs automated review.
• Have experience designing pipelines that handle large media workloads (video-first ideally).
• Are comfortable owning workflows that span infrastructure, product usage, and user-facing behavior.

What You Bring

• Master's degree or higher in Computer Science, Engineering, Mathematics, or AI-related fields.

• Proficiency in Python and data analysis.

• Prior experience leading LLM projects.

• Exceptional communication skills: ability to convey complex technical concepts clearly.

• Strong project management and organizational skills.

• Passion for AI and the intersection of technology, product, and customer needs.

Minimum Qualifications

• Strong experience with Python and backend APIs.
• Experience with production-grade data pipelines or workflow engines.
• Experience with robotics datasets (video, depth, LiDAR, telemetry, pose).
• Experience with evaluation, scoring, or reliability systems.
• Experience with cloud environments (GCP/AWS preferred).

Bonus Qualifications

• Prior work with robotic perception or manipulation datasets.
• Knowledge of dataset versioning and lineage tracking.
• Experience with cost optimization around video lifecycle or automated review systems.
• Experience designing contributor ramp-down or trust-score systems.

Why This Role Matters

This role has direct financial and model-quality impact. Scaling robotics programs without structured workflows results in exponentially increasing QA spend, storage cost, and rework cycles. Your systems allow robotics customers to confidently scale data throughput from tens → thousands → tens of thousands of labeled sequences without compromising reliability.

You are the backbone of robotics execution at Labelbox.

Alignerr Services at Labelbox

As part of the Alignerr Services team, you'll lead implementation of customer projects and manage our elite network of AI experts who deliver high-quality human feedback crucial for AI advancement. Your team will oversee 250,000+ monthly hours of specialized work across RLHF, complex reasoning, and multimodal AI projects, resulting in quality improvements for Frontier AI Labs. You'll leverage our AI-powered talent acquisition system and exclusive access to 16M+ specialized professionals to rapidly build and deploy expert teams that help customers, which include the majority of leading AI labs and AI disruptors, achieve breakthrough AI capabilities through precisely aligned human data—directly contributing to the critical human element in advancing artificial intelligence.

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

$140,000 - $200,000 USD

Life at Labelbox

• Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland
• Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility
• Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making
• Growth: Career advancement opportunities directly tied to your impact
• Vision: Be part of building the foundation for humanity's most transformative technology

Our Vision

We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs.

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.

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 email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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