# Forward Deployed Research Scientist

**Company**: Labelbox
**Location**: San Francisco Bay Area
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $140,000-$200,000 USD
**Category**: Research
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/labelbox/jobs/5101375007?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_e060e82b-395

## Description

## Shape the Future of AI

At Labelbox, we're building critical infrastructure for breakthrough AI models at leading research labs and enterprises. Since 2018, we've pioneered data-centric approaches fundamental to AI development.

## Role Overview

The Forward Deployed Research Team at Labelbox sits at the intersection of research science and client delivery. You will work on multiple client engagements simultaneously, operating on timescales of days to weeks. Your responsibilities include engaging with frontier lab research teams, developing a deep scientific understanding of client engagements, running ablation studies, consulting on workflow and quality systems, and collaborating with the Applied Research team.

## Your Impact

- Engage directly with frontier lab research teams in client scoping meetings, discussing methodology and shaping project specifications.

- Develop a deep scientific understanding of client engagements, building working models of client architecture, training methodology, and target capabilities.

- Run ablation studies and fine-tune open-weight models to empirically measure the impact of data on model performance.

- Consult on workflow and quality systems, ensuring that annotation schemas, task designs, and quality rubrics are technically sound.

- Collaborate with Applied Research on publications and benchmarks, contributing to joint projects and driving them to completion.

## What You Bring

- MS or PhD in Machine Learning, NLP, Computer Science, or a related quantitative field.

- Hands-on experience fine-tuning large language models (open-weight models such as Llama, Mistral, Qwen, or similar).

- Strong understanding of LLM training pipelines , pretraining, supervised fine-tuning, RLHF/DPO, and how data quality and composition affect each stage.

- Experience designing and executing experiments with rigor , hypothesis formation, controlled comparisons, statistical analysis of results.

- Ability to operate at speed, going from problem definition to experimental results in days, not months.

- Strong written and verbal communication, presenting findings to client research teams and contributing to published work.

## Benefits

- High-impact environment with expanded responsibilities and career growth tied to contributions.

- Technical excellence, working at the cutting edge of AI development.

- Innovation at speed, celebrating ownership, fast delivery, and impact.

- Continuous growth, with every role requiring continuous learning and evolution.

- Clear ownership, with autonomy to execute and drive results.

## Compensation

The expected annual base salary range for United States-based candidates is $140,000-$200,000 USD.

## Skills

### Required
- Machine Learning
- NLP
- Computer Science
- LLM training pipelines
- Experiment design
- Statistical analysis
- Communication

### Nice to have
- Prior experience at a frontier AI lab
- Experience with evaluation and benchmarking of LLMs
- Familiarity with human data pipelines
- Experience with reinforcement learning
- Published research in ML/NLP

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/labelbox/jobs/5101375007?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)