---
title: 'Foundation Model Data Engineer at Sciforium'
canonical: 'https://feeny.ai/job/foundation-model-data-engineer-sciforium-san-francisco-w0a2nh2sd3z0'
type: 'job'
last_seen: '2026-09-06'
---

# Foundation Model Data Engineer at Sciforium

- **Company:** Sciforium
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-01-07
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/sciforium/8c52730f-a9ae-412f-914f-3f700622c34b

## Job description

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. 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.

## ROLE OVERVIEW

Sciforium is seeking a highly technical and visionary Foundation Model Data Engineer to lead the strategy, creation, and curation of the massive datasets that power our foundation models. We believe that in the era of LLMs, data is the primary competitive advantage. In this role, you will own the end-to-end data lifecycle—from raw web-scale crawling to the fine-grained human-alignment datasets that define model behavior.

This position is ideal for a scientist who views data as a high-scale engineering challenge and an analytical puzzle. You will not just "provide" data; you will design the taxonomies, filtering heuristics, and post-training pipelines that ensure our models are world-class in reasoning, safety, and multimodal understanding.

## KEY 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).
- Multimodal Expansion: Drive the acquisition and processing of vision and video data, navigating the complexities of multimodal alignment, video compression, and temporal data consistency.
- High-Performance Engineering: Develop high-throughput data processing scripts using Python, leveraging multiprocessing and multithreading to handle massive-scale ingestion and transformation without bottlenecks.
- Data Profiling & Analysis: Conduct deep-dive statistical analysis on training corpora to identify biases, gaps in knowledge, and quality regressions, ensuring the "diet" of the model is mathematically balanced.
- 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.

## MUST-HAVES

- 5+ years of industry experience in Data Science or Machine Learning, with a proven track record of building and managing datasets for foundation models.
- 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.
- Petabyte-Scale Experience: Demonstrated experience working with petabyte-scale datasets that have been directly used to train production-grade LLMs or Large Vision Models.
- 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.
- Data Tooling: Mastery of data-at-scale frameworks such as Spark, Ray, or high-performance data-loading formats (e.g., WebDataset, Parquet).

## NICE-TO-HAVES

- Computer Vision (CV) Curation: Experience building large-scale image or video datasets from scratch (e.g., LAION-style pipelines).
- Multimodal Crawling: Familiarity with large-scale crawling of multimodal data and the associated challenges of video processing, codecs, and compression.
- Taxonomy Design: Experience in designing complex labeling schemas for reasoning, coding, and mathematical benchmarks.
- Research Background: A Master’s or PhD in a quantitative field with a focus on data-centric AI or information retrieval.

## BENEFITS INCLUDE

- Medical, dental, and vision insurance
- 401k plan
- Daily lunch, snacks, and beverages
- Flexible time off
- Competitive salary and equity

## 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.

## About Sciforium

## Company Overview
- **One-liner**: Sciforium is building a vertically integrated AI infrastructure platform that owns its hardware (AMD GPUs) to deliver cost-effective, high-performance inference and foundation model training across text, image, video, and audio modalities.
- **Entity Type**: Private (Seed Stage)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Hassan Akbari

## Core Business
- **Primary Industry**: AI Infrastructure / Generative AI
- **Target Customers**: B2B; AI teams and enterprises that need scalable, multimodal AI inference and model serving without managing their own infrastructure.
- **Mission**: To rebuild AI serving infrastructure from the ground up—owning the hardware and optimizing the entire pipeline end to end—so that any team, regardless of size or budget, can access the best AI capabilities across every modality without compromise.

## Products & Services
- **AI Inference API**: A drop-in replacement for the OpenAI API format, supporting streaming, tool use, structured outputs, and async generation. Runs on Sciforium’s own AMD hardware for lower cost and stronger privacy.
- **Evaluation Platform**: Built-in pipelines to monitor model performance in real time, catch regressions, and benchmark across models.
- **Native Agents Infrastructure**: Serverless platform for running AI agents at scale without managing servers.
- **Model Library**: Access to state-of-the-art open-source models across text, image, video, and audio (e.g., DeepSeek, Wan2, speech models).

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total Funding of $3.9M (Seed round closed June 2024)
- **Notable Investors/Partners**: Backed by AMD and SignalFire
- **Growth Signals**: Headcount grew 160% YoY to 8 employees; 10 active job postings as of mid-2025; 99.98% uptime claimed; N+1 power and N+2 cooling redundancy with liquid-cooled infrastructure.

## Competitive Advantages
- **Vertical Integration**: Owns its own AMD hardware and runs its own data centers, removing intermediaries and markups—leading to lower costs and predictable performance.
- **Multimodal Native**: Built from the ground up to handle text, image, video, and audio in a single API, unlike many competitors that focus on text-only.
- **Privacy & Control**: By running on dedicated infrastructure (not shared servers), customers get stronger data privacy guarantees.
- **High Ambition Culture**: Team includes alumni from Google DeepMind, Microsoft, Amazon, Snowflake, Qualcomm, and Columbia University.

## Strategic Focus
- **Infrastructure Ownership**: Continuing to invest in its own AMD GPU clusters and data center operations to maintain cost and performance advantages.
- **Multimodal Expansion**: Scaling support for all data types (text, image, video, audio) with a single API.
- **Agent Readiness**: Building native support for AI agents at scale.
- **Open-Source Ecosystem**: Supporting the latest open-source models on day one.

## Why Work Here
- **Culture**: Highly independent, self-motivated, and creative environment. Small enough that your work is visible from day one. Principles include relentless quality, outcome ownership, and high ambition.
- **Work Policy**: Hybrid and in-office roles available. Offices in San Francisco (HQ) and Los Altos, California.
- **Team**: Small, high-caliber team with deep experience from Google DeepMind, Snowflake, Amazon, Qualcomm, and other top AI/infra companies.
- **Perks**: Work on hard infrastructure problems that matter, at a company backed by AMD and SignalFire. Opportunity to shape the foundation of AI infrastructure from an early stage.

## Sources
1. [sciforium.com](https://sciforium.com/)
2. [sciforium.com/company](https://sciforium.com/company)
3. [linkedin.com/company/sciforium](https://www.linkedin.com/company/sciforium)
4. [builtin.com/company/sciforium](https://builtin.com/company/sciforium)
5. [jobs.ashbyhq.com/sciforium](https://jobs.ashbyhq.com/sciforium)

## Other roles at Sciforium

- [Pre-training Research Engineer](https://feeny.ai/job/pre-training-research-engineer-sciforium-san-francisco-qqxzt72sswez) — San Francisco, CA
- [Research Engineer - Model Evaluation & MLOps](https://feeny.ai/job/research-engineer-model-evaluation-mlops-sciforium-san-francisco-j6bk6vmfyth9) — San Francisco, CA
- [Growth Marketing Specialist](https://feeny.ai/job/growth-marketing-specialist-sciforium-san-francisco-j384x6r54x22) — San Francisco, CA
- [GPU Kernel Engineer](https://feeny.ai/job/gpu-kernel-engineer-sciforium-san-francisco-xm87qw2qrrt1) — San Francisco, CA
- [Distributed Training and Inference Engineer](https://feeny.ai/job/distributed-training-and-inference-engineer-sciforium-san-francisco-13qdzh34vrwv) — San Francisco, CA
- [Data Center Real Estate & Development Specialist](https://feeny.ai/job/data-center-real-estate-development-specialist-sciforium-san-francisco-vhap3ehmva96) — San Francisco, CA
- [Technical Recruiter](https://feeny.ai/job/technical-recruiter-sciforium-san-francisco-k4sc03ac3z5r) — San Francisco, CA
- [Lead Software Engineer, Model Serving Platform](https://feeny.ai/job/lead-software-engineer-model-serving-platform-sciforium-san-francisco-sbdhk82sxhx3) — San Francisco, CA
- [Software Engineer, Fullstack](https://feeny.ai/job/software-engineer-fullstack-sciforium-san-francisco-w1txtdc4f5gz) — San Francisco, CA
- [GPU Cluster Engineer, Networking](https://feeny.ai/job/gpu-cluster-engineer-networking-sciforium-san-francisco-594atsvfkbpv) — San Francisco, CA