Labelbox · 2 months ago
Applied Research Engineer
San Francisco Bay Area
Full-time
Onsite
Mid Level
$250K/yr - $300K/yr
3+ years expLabelbox is pioneering data-centric approaches that are fundamental to AI development, building critical infrastructure for AI models at leading research labs and enterprises. As an Applied Research Engineer, you will develop advanced systems to create and leverage high-quality human-in-the-loop data, enhancing AI training processes and driving innovation in AI alignment techniques.
Artificial Intelligence (AI)Computer VisionData Collection and LabelingEnterprise SoftwareMachine LearningSoftware
Responsibilities
Advance the field of AI alignment by developing cutting-edge methods, such as RLHF and novel approaches, that ensure AI systems reflect human preferences more accurately
Improve the quality of human-in-the-loop data by designing and deploying rigorous measurement and enhancement systems, leading to more reliable AI training
Increase efficiency and effectiveness in AI-assisted data labeling by creating tools that leverage active learning and adaptive sampling, reducing manual effort while improving accuracy
Shape the next generation of AI models by investigating how different types of human feedback (e.g., demonstrations, preferences, critiques) impact model performance and alignment
Optimize human feedback collection by developing novel algorithms that enhance how AI learns from human input, improving model adaptability and responsiveness
Bridge research and real-world application by integrating breakthroughs into Labelbox’s product suite, making human-AI alignment techniques scalable and impactful for users
Drive industry innovation by engaging with customers and the broader AI community to understand evolving data needs and share best practices for training frontier models
Contribute to the AI research ecosystem by publishing in top-tier journals, presenting at leading conferences, and influencing the future of human-centric AI
Stay ahead of AI advancements by continuously exploring new frontiers in human-AI collaboration, human data quality, and AI alignment, keeping Labelbox at the cutting edge
Establish Labelbox as a thought leader in AI by creating technical documentation, blog posts, and educational content that shape the industry's approach to human-centric AI development
Qualification
Required
A strong foundation in AI and machine learning, backed by a Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field
Proven experience (3+ years) in solving complex ML challenges and delivering impactful solutions that improve real-world AI applications
Expertise in designing and implementing data quality measurement and refinement systems that directly enhance model performance and reliability
A deep understanding of frontier AI models—such as large language models and multimodal models—and the human data strategies needed to optimize them
Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow to prototype and develop cutting-edge solutions
A track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community
The ability to bridge research and application by interpreting new findings and rapidly translating them into functional prototypes
Strong analytical and problem-solving skills that enable you to tackle ambiguous AI challenges with structured, data-driven approaches
Exceptional communication and collaboration skills, allowing you to work effectively across multidisciplinary teams and with external stakeholders
Benefits
Equity packages
Career advancement opportunities directly tied to your impact
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