Applied Research Engineer (Agents)

Labelbox

San Francisco (CA)

On-site

USD 250,000 - 300,000

Full time

14 days+

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Benefits offered by this job

Career growth tied to contributions

Hybrid work model

Innovative work environment

Job summary

A cutting-edge AI development company in San Francisco seeks a talented researcher to advance autonomous agent capabilities. You will design data programs and collaborate with leading AI research teams. Candidates should hold a Ph.D. or Master's in a related field with strong experience in machine learning. The position offers a hybrid work model, competitive salary, and opportunities for career growth aligned with contributions.

Qualifications

3+ years of experience addressing sophisticated ML problems with successful delivery.
Constructed and evaluated agentic benchmarks and reliability/efficiency suites.
Track record of publications in top-tier AI/ML venues.

Responsibilities

Create frameworks and tools to evaluate autonomous agent capabilities.
Design data programs using reinforcement learning methodologies.
Engage with AI research teams to understand evolving data needs.

Skills

Analytical skills

Problem-solving abilities

Team collaboration

Python proficiency

Deep learning frameworks (PyTorch, TensorFlow)

Education

Ph.D. or Master's degree in Computer Science, Machine Learning, AI

Tools

PyTorch

TensorFlow

JAX

Job description

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:

Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale
Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models
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

Your Impact

Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities.
Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies.
Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models.
Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices.
Collaborate closely with frontier AI lab customers to understand requirements and guide model development.
Publish research findings in academic journals, conferences, and blog posts.

What You Bring

Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field.
At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers.
Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).
Adept at interpreting research literature and quickly turning new ideas into prototypes.
Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements.
Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).
Strong analytical and problem-solving abilities in ambiguous situations.
Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.).

Labelbox Applied Research

At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios.

We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidatesis 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

$250,000 - $300,000 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 @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.

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