We're looking for an ML engineer to own the entire machine learning lifecycle behind Jarmin's AI employees including researching techniques, engineering features, training and evaluating models, and deploying them to production. This is the machine learning at the heart of the product, and from day one you'll own real projects that define what it can do.

In any given week you'll be:

• Responsible for reliability of unsupervised ML. Own the pipelines, training, and inference that run across many use cases
• Building eval infrastructure and online/offline metrics
• Build feature engineering, model selection, and tuning given rapidly changing needs
• Research new techniques and bring them into production

Ideally you:

• Have deep, hands on experience taking ML models from data to production
• Have strong software engineering fundamentals and write clean, reliable, production grade code
• Stay close to new AI/ML research and bring what works into real systems
• Turn vague problems into clear action items and ship constantly
• Hold a high bar and own the quality of everything you touch
• Love in-person team culture (we're in San Francisco)

Team Culture:

• We're small, in-person, resourceful, and building the future we want to live in
• We give feedback early and often, so you always know where you stand and where you're headed

About Jarmin

Jarmin.ai builds AI employees for human-level roles. It learns its responsibilities, understands your data, embeds into your systems, and becomes part of your team's day-to-day workflow. Completely hand over full initiatives or individual tasks.

Hire AI ML Engineers, Account Executives, Paralegals, Financial analysts, Compliance analysts, and more.

Jarmin’s founding team is from Meta SuperIntelligence Labs (Staff Engineers), Apple (Machine Learning Engineer), AWS (scaling infra), Lockheed-Martin (Research), and JPMorganChase (SWE) with experience building AI/ML and automating complex work of Researchers, Data Scientists, ML Engineers with AI.

Compensation: $130K - $180K

Skills: Machine Learning

Experience: Any (new grads ok)