Human Data - Engineer

AI Trainer Jobs; United States; Remote; USD 144,000 - 220,000; Full time

Job summary

SpaceXAI, based in the United States, seeks an engineer to secure high-quality data for model training and evaluation. You will partner with model and engineering teams, design data projects, and drive end-to-end delivery of critical data and eval initiatives to accelerate model development.

The role emphasizes data integrity, multimodal data handling, and building robust annotation tools. Weekend work and travel may be required as part of the responsibilities.

Qualifications

• Bachelor's degree in engineering, CS, or STEM field, or 4+ years of equivalent experience.
• Experience collaborating with cross-functional teams (engineering, research, product, or operations).
• Proven ability to analyze datasets to identify trends, anomalies, and data quality issues.

Responsibilities

• Partner with model and engineering teams to translate needs into high-value data projects.
• Own end-to-end delivery of data and evaluation projects that drive training signals.
• Build tools to measure data yield and eval lift and perform evaluations to improve quality.
• Maintain data integrity and truthfulness with rigorous validation processes.
• Research and implement data collection, annotation, generation, and multimodal techniques.
• Shape model behavior through targeted data work and domain-specific improvements.
• Design and improve annotation workflows and labeling interfaces for quality.
• Coordinate with Human Data Ops and stakeholders to scale projects and forecast demand.
• Report status, insights, and blockers to enable rapid decision-making.

Skills

Python

SQL

Data analysis

Cross-functional collaboration

Data quality

Evaluation methods

Education

Bachelor's degree in engineering/computer science or related STEM discipline

Master's degree in a relevant technical field

Tools

Annotation tools

Data workflows

Job description

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 - $220,000 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.