About the role
From the employer’s listing · Palantir · posted 9 May 2024
A World-Changing Company
Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more.
The Role
Forward Deployed AI Engineers work directly with customers owning Gen AI strategy and implementation. On a daily basis, you will build end-to-end workflows, take them to production, and solve real world problems at the largest scale. You will have ample opportunity to contribute learnings from the field back to the Palantir AIP product suite.
You will be on the forefront of extending Palantir's existing footprint and strategy into new markets and problem spaces opened up by Gen AI.
Core Responsibilities
Forward Deployed AI Engineers’ responsibilities look similar to those of a hands-on AI startup CTO: you’ll work in small teams to own delivery of high stakes projects with clients. A day’s work may include building LLM workflows on a large scale, interacting with customers to understand their needs and set their AI strategy, but the most impact will be driven by implementing solutions into the real world of our partner's organisations.
Do you aspire to be an entrepreneur or an Applied AI leader? We believe Palantir is the best place — with the best colleagues — to learn how!
What We Value: Engineering mindset, focused on delivering production solutions with Gen AI, data processing pipelines, and advanced analytics tools. Solving real business problems, not academic benchmarks. Ability to collaborate efficiently in teams of technical and non-technical individuals. Comfort working in a dynamic environment with evolving objectives and direct iteration with users.
What We Require: Past experience building solutions with LLMs and a deep understanding of overall Gen AI landscape. Strong foundation in Machine Learning basics (Evaluation, Training, Problem Decomposition). Strong engineering background. Preferred fields include but are not limited to Computer Science, Mathematics, Software Engineering, Physics, and Machine Learning. Strong coder with demonstrated proficiency in programming languages such as Python, Java, C++, TypeScript/JavaScript, or similar. Ability and interest in travelling up to 25%, as needed to client sites, but flexible based on personal preferences.