Inception creates the world’s fastest, most efficient AI models. Our Mercury model is the world’s fastest reasoning LLM and first commercially available diffusion LLM, delivering 5x greater speed and efficiency than today’s LLMs, with best-in-class quality.

We are the AI researchers and engineers behind such breakthrough AI technologies as diffusion models, flash attention, and DPO.

The Role

We seek experienced engineers to architect and scale the core infrastructure behind distributed training pipelines and petabyte-scale data catalogs. You'll work directly with researchers to accelerate experiments, develop new datasets, improve infrastructure efficiency, and enable key insights across our data assets.

Key Responsibilities

Design, build, and operate scalable, fault-tolerant infrastructure for LLM research: distributed compute, data orchestration, and storage across modalities.
Develop high-throughput systems for data ingestion, processing, and transformation — including training data catalogs, deduplication, quality checks, and search.
Build systems for web crawling, data ingestion, and real-time data processing to support model training operations.
Develop tools and frameworks for efficient data storage, retrieval, and versioning across distributed systems.
Ensure data collection adheres to privacy regulations.

Qualifications

BS/MS/PhD in Computer Science, Machine Learning, or a related field (or equivalent experience).
3+ years of experience building data processing pipelines at scale, particularly with AI/ML applications.
Strong proficiency in Python and experience with data processing frameworks (Apache Spark, Beam, Airflow).
Familiarity with synthetic data generation techniques and data augmentation strategies.
Familiarity with web scraping, crawling technologies, and Common Crawl datasets.
Solid understanding of machine learning fundamentals and experience with ML frameworks (PyTorch, TensorFlow).
Experience with SQL and NoSQL databases for managing structured and unstructured data.

Preferred Skills

Experience with large language models and understanding of tokenization, embeddings, and model architectures.
Experience managing human annotation workflows and quality control processes.
Experience with vector databases and embedding-based retrieval systems.
Knowledge of data privacy regulations and ethical AI practices.
Experience with distributed computing and large-scale data storage systems (HDFS, S3, BigQuery).

Why Join Inception

Work with World-Class Talent: Collaborate with the inventors of diffusion models and leading AI researchers
Shape Foundational Technology: Your decisions will influence how the next generation of AI products are built and used
Immediate Impact: Join at the ground floor where your contributions directly shape product direction and company trajectory

Perks & Benefits

Competitive salary and equity in a rapidly growing startup
Flexible vacation and paid time off (PTO)
Health, dental, and vision insurance
Catered meals (breakfast, lunch, & dinner)
Commuter subsidies
A collaborative and inclusive culture

About Us

Inception creates the world’s fastest, most efficient AI models. Today’s autoregressive LLMs generate tokens sequentially, which makes them painfully slow and expensive. Inception’s diffusion-based LLMs (dLLMs) generate answers in parallel. They are 5x faster and more efficient, while delivering best-in-class quality.

Inception was co-founded by Stanford professor Stefano Ermon, who co-invented such breakthrough AI technologies as diffusion models, flash attention, and DPO, UCLA professor Aditya Grover, who co-invented node2vec, decision transformers, and d1 reasoning, and Cornell professor and Afresh co-founder Volodymyr Kuleshov, who co-invented MDLM and Block Diffusion.

We pioneered the application of diffusion to language, with world’s first (and only) commercially available dLLM, Mercury. We are currently deploying our large-scale diffusion LLMs at Fortune 500 companies. Diffusion is the technology behind today’s image and video AI, and we’re making it the standard for LLMs as well.

Our team includes engineers from AWS, Google DeepMind, Meta AI, Microsoft, HashiCorp, and OpenAI. Based in Palo Alto, CA, we are backed by top-tier venture capitalists, including Menlo Ventures, Mayfield, M12 (Microsoft’s venture fund), Snowflake Ventures, Databricks, and Innovation Endeavors, and by tech luminaries such as Andrew Ng, Andrej Karpathy, and Eric Schmidt.

If you are talented, innovative, and ambitious, come help us invent the future of AI.

We are an equal opportunity employer and encourage candidates of all backgrounds to apply.

Member of Technical Staff, Data Infrastructure