Staff Software Engineer (Machine Learning)

TL;DR

Staff Software Engineer, Machine Learning (AI): Crafting intuitive user experiences powered by generative AI. Focus on shaping impactful AI-driven features that help customers solve real-world problems with greater speed and ease.

Location: Located in San Francisco and open to working in office

Salary: $200,000 - $275,000 Annually + Benefits + Equity (if applicable) + Bonus (if applicable)

Company

hirify.global helps the world’s most complex organizations solve their hardest problems with unprecedented speed and accuracy with their AI-enabled platform.

What you will do

• Deliver differentiated value to customers by crafting powerful, intuitive user experiences powered by generative AI.
• Shape safe, impactful AI-driven features that help customers solve real-world problems with greater speed and ease.
• Scale the platform to handle terabytes of data ingested from a variety of sources.
• Optimize search algorithms to serve results quickly.

Requirements

• Understanding of best practices for using generative AI responsibly, with bonus experience applying LLMs to enhance user experience
• Knowledge of how to train, deploy, integrate, and monitor machine learning models
• Degree in Computer Science or a related field, or equivalent experience
• Over 8 years of experience working with cross-functional software development teams.
• Experience shipping and iterating on production-grade software components professionally and / or in the open-source community
• Ability to write robust, well tested, and well-designed code that frequently gets deployed to users
• Strong best practices in modern software development and comfort navigating large codebases
• Located in San Francisco and open to working in office

Culture & Benefits

• Team values empathy, ownership, collaboration, humility, and perseverance.
• Opportunity to work closely with the team onsite to understand the variety of use cases that hirify.global serves.
• Engineers take full responsibility for major features and work closely with other engineers to drive them to completion.
• Collaborate directly with the deployment team and users as we iterate to solve their problems.