Sciforium

LLM Dataset Engineer

San Francisco

Sponsorship not specifiedDetected 196 days ago

PythonFull-Stack DevelopmentMachine LearningSparkData ScienceComputer VisionLLMsStatisticsResearch

About the role

We believe that in the era of LLMs, data is the primary competitive advantage.
This position is ideal for a scientist who views data as a high-scale engineering challenge and an analytical puzzle.

Responsibilities

Foundation Dataset Strategy: Own the end-to-end creation of pre-training datasets for LLMs. This includes defining the mix of web data, code, books, and technical papers to optimize for downstream model performance.
Petabyte-Scale Curation: Design and implement sophisticated pipelines for data cleaning, exact/fuzzy deduplication, and high-quality signal extraction from petabytes of raw, unstructured data.
Post-Training & Alignment Data: Lead the development of high-quality post-training datasets, including Supervised Fine-Tuning (SFT) instructions, multi-turn dialogues, and preference modeling data (RLHF/DPO).
High-Performance Engineering: Develop high-throughput data processing scripts using Python, leveraging multiprocessing and multithreading to handle massive-scale ingestion and transformation without bottlenecks.
Synthetic Data Generation: (Added Value) Design pipelines to generate high-reasoning synthetic data to augment gaps in natural datasets, utilizing existing models for data labeling and refinement.
Dataset Reconstruction: Experience building massive LLM training sets from scratch, including raw web crawls (e.g., Common Crawl) and specialized domain data.
Post-Training Expertise: Hands-on experience building datasets for RLHF, DPO, and multi-turn instruction following, including the management of human-labeling workflows and quality gold-sets.
Foundation Dataset Strategy: Own the end-to-end creation of pre-training datasets for LLMs.
Experience building large-scale image or video datasets from scratch (e.g., LAION-style pipelines).

Requirements

Familiarity with large-scale crawling of multimodal data and the associated challenges of video processing, codecs, and compression.
Deep Proficiency in Python: Expert-level skills with a focus on high-performance code, including multiprocessing, multithreading, and efficient memory management for large-scale data tasks.

Skills

Mastery of data-at-scale frameworks such as Spark, Ray, or high-performance data-loading formats (e.g., WebDataset, Parquet).

Compensation

Competitive salary and equity

Benefits

Medical, dental, and vision insurance
Flexible time off
Competitive salary and equity
Drive the acquisition and processing of vision and video data, navigating the complexities of multimodal alignment, video compression, and temporal data consistency.
Demonstrated experience working with petabyte-scale datasets that have been directly used to train production-grade LLMs or Large Vision Models.
5+ years of industry experience in Data Science or Machine Learning, with a proven track record of building and managing datasets for foundation models.

Equal opportunity

Sciforium is an equal opportunity employer.
All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Visa & Work Authorization

Backed by multi-million-dollar funding and direct sponsorship from AMD with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications.

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This listing is sourced directly from Sciforium's careers page and normalized into a canonical job model.