Early-stage, cybersecurity investment (valued over $100M at Seed), founded by a successful serial entrepreneur, is looking to hire a Founding MLE with a strong background standing up training/inference pipelines in the cloud (GCP/AWS), good MLOps familiarity, and full end-to-end ownership.

Summary:

Help architect the core ML pipelines and codebase for an industry-first solution in security. Our ideal candidate will be able to take research-grade ML experiments and ensure they can be run in a stable and repeatable manner in the enterprise.

Key Qualifications:

Advanced degree in CS (or a related field) with 4+ years industry experience and 1+ years working with LLM's in a large-scale production environment
Prior experience with a zero-to-one
Proven ability to collaborate across different teams and adapt to new fields

Model Training Responsibilities:

Design and train machine learning models from scratch, developing and testing new architectures on large, complex datasets
Build and optimize end-to-end training pipelines, including data preprocessing, distributed training, and experiment tracking
Tune and evaluate model performance through systematic experimentation, hyperparameter optimization, and metric analysis
Collaborate with data and infrastructure teams to manage compute resources, ensure reproducibility, and prepare models for deployment

Please note:

There are no fees associated with any of the support we provide our investments. Greylock Talent provides free candidate referrals/introductions to all of our active investments (one of the many services we provide).

Due to the volume of applicants we typically receive, a follow-up email will not be sent unless a match is identified.

Founding Machine Learning Engineer