Operations Engineer - Human Data

Xai

Palo Alto, CA

On-site

Who this role is best for

A natural match if you have experience curating training data for AI systems and thrive in a collaborative, flat-structured environment.

Best fit for

Candidates with experience in dataset curation and a background in AI/ML systems
— “Direct experience curating, evaluating, or improving training or evaluation datasets for large language models or other AI/ML systems”
Individuals who excel in cross-functional collaboration and communication
— “All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.”
Engineers who prioritize data quality and are comfortable with data validation processes
— “Maintain rigorous data integrity and truthfulness, including validation processes for factual accuracy; prioritize quality over quantity.”

Things to consider

Weekend work and potential travel to other sites may be required
— “Weekend work may be required.”
This is a hands-on role with direct contribution to the company’s mission
— “All employees are expected to be hands-on and to contribute directly to the company’s mission.”

How to stand out

Highlight experience in building annotation tools and improving labeling workflows
— “Experience designing, supporting, or optimizing annotation tools, labeling interfaces, or data workflows that prioritize factual accuracy and data integrity”
Emphasize your ability to translate engineering needs into data projects
— “Partner with model and engineering teams to understand needs and translate them into high-value data projects and evaluation strategies.”
Showcase skills in analyzing datasets for quality and integrity issues
— “Demonstrated experience analyzing datasets to identify trends, anomalies, quality issues, or integrity problems”
Demonstrate your ability to measure data effectiveness and improve it iteratively
— “Build tools and systems to measure data effectiveness (data yield, eval lift, usage), and run evaluations yourself to continuously improve quality.”
Demonstrate your capacity to shape AI behavior through data work
— “Shape Grok’s behavior and domain performance through targeted data work.”

Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · IndividualLevel · Mid

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

high-quality data projects
improved data yield

Typical background

data engineeringAI data curation

Skills & requirements

Required

Data EngineeringAI Data ProjectsData IntegrityData Collection

Preferred

Multimodal Data HandlingLarge Language Model Evaluation

Stack & domain

PythonNode.jsSQLC/c++JavaC#Multimodal DataAIMLCommunicationLeadershipProblem-solvingMongodb CertificationCloud Provider CertificationData Engineering

About the role

Original posting from Xai via Greenhouse

SpaceXAI’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. 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 employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
ABOUT THE ROLE:
You will ensure engineering teams get the right data they need—high-quality tasks and evaluations—by crafting and executing high-value Human Data projects. You sit at the intersection of engineering and data operations: partnering with model teams, designing projects that capture meaningful signals, and driving data yield and eval lift. This is a hands-on technical role for engineers who deeply understand training and evaluation and want to influence data strategy.
RESPONSIBILITIES:
Partner with model and engineering teams to understand needs and translate them into high-value data projects and evaluation strategies.
Own end-to-end delivery of critical data and eval projects that capture meaningful training signals and support rapid model development.
Build tools and systems to measure data effectiveness (data yield, eval lift, usage), and run evaluations yourself to continuously improve quality.
Maintain rigorous data integrity and truthfulness, including validation processes for factual accuracy; prioritize quality over quantity.
Research, implement, and evaluate techniques for data collection, annotation, generation, and multi-modal integration.
Shape Grok’s behavior and domain performance through targeted data work.
Design and improve annotation workflows, labeling interfaces, and related tools with a focus on data quality and integrity.
Act as a liaison between engineering, technical staff, and tutoring / Human Data teams to drive alignment and knowledge sharing.
Collaborate with Human Data Ops and stakeholders to scale projects, share learnings, and contribute to demand forecasting; report status, insights, and blockers for rapid decisions.
BASIC QUALIFICATIONS:
Bachelor’s degree in engineering, computer science, or a related STEM discipline, or 4+ years of experience in lieu of a degree
Experience collaborating with cross-functional teams (engineering, research, product, or annotation/operations groups)
Demonstrated experience analyzing datasets to identify trends, anomalies, quality issues, or integrity problems
PREFERRED SKILLS AND EXPERIENCE:
Master’s degree or higher in a relevant technical field
Direct experience curating, evaluating, or improving training or evaluation datasets for large language models or other AI/ML systems
Experience designing, supporting, or optimizing annotation tools, labeling interfaces, or data workflows that prioritize factual accuracy and data integrity
Familiarity with multimodal data (text + images, code, or other modalities) or domain-specific data (science, mathematics, programming, recent events, etc.)
Experience conducting model or dataset evaluations focused on quality, truthfulness, or alignment with product goals
Experience in a scripting language like Python
Experience in SQL or other data analysis tools
ADDITIONAL REQUIREMENTS:
Weekend work may be required.
Travel to other SpaceXAI sites may be required.
COMPENSATION AND BENEFITS:
$144,000 - $270,000 USD
Base salary is just one part of our total rewards package at SpaceXAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Source: Xai careers (Greenhouse)