Labelbox · 4 months ago
Applied Research Engineer, Agents
San Francisco Bay Area
Full-time
Onsite
Mid Level
$250K/yr - $300K/yr
3+ years expLabelbox is pioneering data-centric approaches fundamental to AI development, providing integrated solutions for frontier AI development. The Applied Research Engineer role focuses on advancing capable, adaptable agents through data landscape creation, utilizing methodologies like supervised fine-tuning and reinforcement learning, and collaborating with leading AI research teams.
Artificial Intelligence (AI)Computer VisionData Collection and LabelingEnterprise SoftwareMachine LearningSoftware
Responsibilities
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
Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems
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
Qualification
Required
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
Experience building and training autonomous agents—tool use, structured outputs, multi-step planning—across browsers/GUI, codebases, and databases using SFT and RL
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
Excellent communication skills
Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.)
Company
Labelbox
Labelbox is the leading data factory for AI teams.
51-200 employees
H1B Sponsorship
Labelbox has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (12)
2024 (6)
2023 (6)
2022 (7)
2021 (3)
2020 (3)
Funding
Current Stage
Late StageTotal Funding
$188.9MKey Investors
SoftBank Vision FundAndreessen HorowitzGradient
2022-01-06Series D· $110M
2021-02-11Series C· $40M
2020-02-04Series B· $25M
Leadership Team
Manu Sharma
CEO & Co-founder
Recent News
2025-11-02
2025-06-20
Company data provided by crunchbase