Founding Machine Learning Engineer

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.