Skills & Technologies
Requirements
- Experience
- 3+ years
- Education
- Master's degree
Benefits
Joblaze summary
In the role of Applied Research Engineer at Labelbox, the individual will focus on developing advanced systems that integrate human feedback into AI training processes, enhancing the quality of human-in-the-loop data. Key skills include expertise in machine learning, proficiency in Python, and experience with frameworks like PyTorch or TensorFlow. This position is ideal for someone with a strong academic background and at least three years of practical experience in AI, particularly in frontier model training and data quality enhancement. Labelbox fosters a high-impact, collaborative environment that encourages innovation and rapid execution.
Joblaze insights
- Listed about a month ago on Joblaze — tracked directly from Labelbox's career page.
- Labelbox has 9 other open roles including Forward Deployed Engineer Intern, Forward Deployed Engineering Manager, Managing Partner, Frontier AI.
- 2358 active Python roles on Joblaze right now.
- 160 active PyTorch roles on Joblaze right now.
- 72 active TensorFlow roles on Joblaze right now.
- Salary band is above the typical range for AI/ML (median ~$190,000).
Quick facts
- Is the Applied Research Engineer role remote?
- It's hybrid — Labelbox expects some on-site time in San Francisco Bay Area.
- What's the salary range?
- Labelbox lists $250,000–$300,000 for this role.
- How much experience is required?
- At least 3 years of relevant experience for this Applied Research Engineer role.
- Where is the role based?
- Labelbox is hiring for this position in San Francisco Bay Area.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Multimodal Models, Direct Preference Optimization (DPO), JAX, Large Language Models, Reinforcement Learning from Human Feedback (RLHF), PyTorch.
- What seniority level is this role?
- Labelbox targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Applied Research Engineer role at Labelbox.
From the original posting
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:
- 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
Applied Research at Labelbox builds the benchmarks and data that drive the next generation of foundational agentic capabilities. We are looking for exceptional researchers and research engineers to join our team to measure and improve agent performance while collaborating directly with our frontier lab research partners.
Your Impact
- Define benchmarks and training signals to push agentic capabilities forward.
- Conduct research to ensure evaluations and data are insightful and reliable.
- Propose and collaborate on experiments and projects with research teams at frontier labs for their evaluation and training needs.
- Drive ambiguous research threads autonomously.
- Turn research insights into concrete opportunities.
- Stay current with the latest developments in agentic capabilities, training, and evaluation methodologies.
- Publish research findings and contribute to the broader research community.
What You Bring
- 2+ years of industry experience in ML, with an MS, PhD, or equivalent research track record in CS / ML / a related field.
- Track record of published papers in top venues (e.g. NeurIPS, ICML, ACL, EMNLP)
- Strong understanding of experimental design, statistical analysis, and evaluation frameworks
- Self-directed individual with strong communication skills
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 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.
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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