# Forward Deployed Research Scientist

**Company:** [Labelbox](https://hotfix.jobs/companies/labelbox)
**Location:** San Francisco, CA
**Role:** AI Research
**Salary:** $140k – $200k/yr
**Skills:** Machine Learning, LLMs, Fine-Tuning, Llm Training Pipelines, RLHF, Dpo, Ablation Studies, Experiment Design, Statistical Analysis, Evaluation Frameworks, Benchmarking, Annotation Workflows, Llama, Mistral, Qwen
**Posted:** 2026-04-13

> Forward Deployed Research Scientist collaborates with frontier AI labs on data strategies, fine-tunes open-weight LLMs, runs ablation studies, and validates data impact for client projects. Requires MS/PhD in ML/NLP/CS, hands-on LLM fine-tuning, and fast-paced experimental rigor.

## Job Description

## Responsibilities

- Engage directly with frontier lab research teams in scoping meetings, challenge assumptions, and shape project specifications based on data composition effects on model outcomes.
- Develop deep scientific understanding of client architectures, training methodologies, and target capabilities to reason about data strategies, identify risks, and iterate empirically.
- Run ablation studies and fine-tune open-weight models on client data to validate data impact on model performance.
- Consult on workflow and quality systems, reviewing annotation schemas, task designs, and quality rubrics with Human Data Operations.
- Collaborate with Applied Research on publications, benchmarks, white papers, and conference submissions using client-grounded findings.

## Requirements

**Required:**
- MS or PhD in Machine Learning, NLP, Computer Science, or related quantitative field.
- Hands-on experience fine-tuning large language models (e.g., Llama, Mistral, Qwen).
- Strong understanding of LLM training pipelines (pretraining, supervised fine-tuning, RLHF/DPO) and data quality/composition effects.
- Experience designing/executing rigorous experiments (hypothesis formation, controlled comparisons, statistical analysis).
- Ability to operate at speed (problem to results in days).
- Strong written/verbal communication for client presentations and publications.

**Strongly Preferred:**
- Experience at frontier AI lab, applied ML startup, or research with client interaction.
- LLM evaluation/benchmarking (metrics, eval harnesses).
- Human data pipelines (annotation workflows, quality assurance, inter-annotator agreement).
- Reinforcement learning, reward modeling, or RLHF.
- Published ML/NLP research.

**What Matters:**
- Applied instinct, comfort with ambiguity, cross-functional fluency, intellectual honesty.

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