Enterprise API - Applied AI Engineer

San Francisco & Palo Alto, CA •

4 days ago

machine learning

RAG

LLM

Share:

About xAI

xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.

Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. Engineers are encouraged to work across multiple areas of the company, and as a result, all engineers and researchers share the title "Member of Technical Staff."

We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important.

All engineers and researchers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

About the Role

Enterprise API - Applied AI Engineers work directly with our end customers owning strategy and execution. Your responsibilities look similar to that of a hands-on AI startup CTO: you’ll work in a small team to own delivery of high stakes projects with clients. A day’s work may include:

Deliver solutions end to end that meet the needs of our customers - understanding user pain points, scoping product specs, and designing and building LLM-powered software
Benchmarking the model or help write evals for customers to identify model weaknesses
Improve model performance by system prompt tuning or fine tuning models
Analyze request logs or read through prompt data
Build internal tooling to automate yourself out of the job
Improving xAI SDKs or developer documentation based on customer feedback

Focus

Strong passion for solving real-world business problems and delivering measurable impact through AI solutions.
Proven track record of shipping high-quality code and successfully completing projects in challenging environments.
Ability to navigate ambiguity and adapt to changing requirements and priorities in a fast-paced startup environment.
Strong communication skills that will become important when interfacing with customers to clarify requirements and drive a project to completion.
Emphasis on designing, implementing, and maintaining robust and scalable AI-driven solutions.
Proficiency in working with large, complex codebases and designing efficient data processing and model serving architectures

An ideal candidate meets at least the following requirements:

2+ years of software engineering experience preferred
Great verbal and written communication skills in English
Ability to turn business and product ideas into engineering solutions
Proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces
Experience in Python and/or TypeScript
Understanding of the HTTP protocol
Strong engineering background, preferred in fields such as Computer Science, Mathematics, Software Engineering, Physics, and Data Science

Furthermore, candidates may stand out by having any of the following experiences:

Building evals for new capabilities and evaluating our systems
Demonstrating an understanding of machine learning fundamentals, including model evaluation, training and fine-tuning
Deploying machine learning models to production
Writing developer documentation
Creating and maintaining SDKs
Showcasing the ability to work with massive datasets, optimize performance, and scale systems to handle high-throughput workloads
Using Pulumi or Terraform

Interview Process

After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15 minute interview (“technical phone interview”) during which a member of our team will ask technical questions about your background or specialization. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews:

Coding assessment in a language of your choice.
Systems hands-on: Demonstrate practical skills in a live problem-solving session.
Project deep-dive: Present your past exceptional work to a small audience.
Meet and greet with the wider team.

Our goal is to finish the main process within one week. We don’t rely on recruiters for assessments. Every application is reviewed by a member of our technical team. All interviews will be conducted via Google Meet or in-person.