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Intern World Coffee Research Jobs (NOW HIRING)

Labelbox

Applied Research Intern

San Francisco, CA

Role Overview As an Applied Research intern at Labelbox, you will design, build, and productionize ... Experiment and prototype RLHF/RLAIF/RLVR/RM/DPOstyle training loops to improve real-world task and ...

Fred Hutchinson Cancer Center

Intern, Research

Seattle, WA · On-site

$21.30 - $30.13/hr

We seek employees who bring different and innovative ways of seeing the world and solving problems ... The Research Intern will support ongoing studies in the laboratory of Neelendu Dey focused on the ...

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How much do intern world coffee research jobs pay per month?

As of May 28, 2026, the average monthly pay for intern world coffee research in the United States is $6,439.50, according to ZipRecruiter salary data. Most workers in this role earn between $4,416.67 and $7,666.67 per month, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Intern at World Coffee Research, and why are they important?

To thrive as an Intern at World Coffee Research, you generally need a background in agriculture, plant science, or related fields, often supported by relevant coursework or ongoing undergraduate/graduate studies. Familiarity with research tools, data collection methods, and basic software like Microsoft Excel or statistical programs is valuable. Strong communication, attention to detail, and a proactive attitude help interns collaborate effectively and contribute to research projects. These skills are vital for supporting impactful research, ensuring data accuracy, and fostering teamwork within a scientific environment.

What types of projects or tasks can an Intern at World Coffee Research expect to work on during their internship?

As an Intern at World Coffee Research, you can expect to engage in a variety of hands-on projects that support scientific research on coffee quality, sustainability, and crop resilience. Typical tasks may include assisting with data collection and analysis, helping organize field trials, preparing research summaries, and supporting communications efforts. You’ll collaborate closely with scientists, agronomists, and program managers, gaining exposure to both lab and fieldwork settings. This experience provides valuable insight into agricultural research and may open pathways for future roles in environmental science or agronomy.

What does an Intern at World Coffee Research do?

An Intern at World Coffee Research assists with various projects supporting the organization's mission to improve coffee quality and sustainability through scientific research. Typical tasks may include data collection and analysis, literature reviews, supporting field trials, and helping to communicate research findings. Interns may work closely with scientists and project managers, gaining hands-on experience in agricultural research, project management, and international development. The internship provides valuable exposure to coffee science and the global coffee industry.

What is the difference between Intern World Coffee Research vs Intern Coffee Quality Assurance?

AspectIntern World Coffee ResearchIntern Coffee Quality Assurance
Primary FocusResearch and development in coffee cultivation, sustainability, and industry innovationEnsuring coffee product quality, testing, and compliance with standards
Work EnvironmentResearch labs, field sites, industry conferencesQuality labs, processing facilities, sensory evaluation labs
Required CredentialsBackground in agriculture, plant science, or related fieldsBackground in food science, quality control, or sensory analysis

Intern World Coffee Research typically involves research-focused work on coffee sustainability and industry innovation, while Intern Coffee Quality Assurance centers on maintaining coffee quality standards through testing and sensory evaluation. Both roles are essential in the coffee industry but differ in their core activities and focus areas.

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Intern World Coffee Research jobs near you
Applied Research Intern

Applied Research Intern

Labelbox

San Francisco, CA

Other

Posted 22 days ago

Job description

Role Overview

As an Applied Research intern at Labelbox, you will design, build, and productionize evaluation and posttraining systems for frontier LLMs and multimodal models. You'll own continuous, high-quality evals and benchmarks (reasoning, code, agent/tooluse, longcontext, visionlanguage, et al.), create and curate posttraining datasets (human + synthetic), and prototype RLHF/RLAIF/RLVR/RM/DPOstyle training loops to measure and improve realworld task and agent performance.

Your Impact
  • Build and own evaluation and benchmark suites for reasoning, code, agents, longcontext, and V/LLMs.
  • Create posttraining datasets at scale: design preference/critique pipelines (human + synthetic), and target hard failures surfaced by evals.
  • Experiment and prototype RLHF/RLAIF/RLVR/RM/DPOstyle training loops to improve real-world task and agent performance.
  • Land research in product: ship improvements into Labelbox workflows, services, and customerfacing evaluation/quality features; quantify impact with customer and internal metrics.
  • Engage with customer research teams: run pilots, codesign benchmarks, and share practical findings through internal research reports, blog posts, talks, and published papers.
What You Bring
  • 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 (in progress degrees are acceptable for intern positions).
  • A deep understanding of frontier autoregressive and diffusion multimodal models, along with the human and synthetic data strategies needed to optimize them.
  • Passion and experience for LLM evaluation and benchmarking.
  • Expertise in training data quality construction, measurement and refinement.
  • The ability to bridge research and application by interpreting new findings and translating them into functional prototypes.
  • 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.
  • Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow.
  • Exceptional communication and collaboration skills.
Applied Research at Labelbox

At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advancing 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.

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