RESPONSIBILITIES
Build AI systems and applications that address engineering and business problems, working with users to understand requirements and define measurable success criteria.
Develop evaluations (evals), benchmarks, and representative datasets to measure model and agent performance, compare approaches, and detect regressions.
Build automated graders and scoring methods, validate their agreement with expert judgments, and investigate misleading results, data leakage, and other evaluation failures.
Create reproducible environments for training and evaluating agents, including task definitions, tool interfaces, constraints, and feedback signals.
Integrate models and agents with engineering tools, internal services, and company data, capturing execution traces and results to support debugging and evaluation.
Establish baselines, run experiments, and analyze failures to determine whether changes to data, models, tools, or workflows produce meaningful improvements.
Develop data preparation, training, and evaluation workflows for problems with limited real-world data, including targeted data collection, labeling, augmentation, and synthetic data where appropriate.
Use Docker and Kubernetes to build and operate reliable workloads with appropriate isolation, access controls, resource management, logging, and reproducibility.
Collaborate with engineering, infrastructure, security, HR, and legal partners to implement requirements for data handling, traceable outputs, auditability, and human review.
Maintain deployed systems through testing, monitoring, ongoing evaluation, and operational debugging, improving quality, reliability, latency, and cost based on evidence and user feedback.
BASIC QUALIFICATIONS
Bachelor’s degree in computer science, data science, engineering, math, or physics; OR 4+ years of professional experience building and training AI/ML systems in lieu of a degree
+1 years of Python programming development and debugging software on Linux.
+1 years of experience with ML framework such as PyTorch, or practical experience developing agents and model-based applications.
+1 years of experience building or evaluating AI/ML systems through professional work, internships, research, or substantial independent projects.
PREFERRED SKILLS AND EXPERIENCE
Understanding of evaluation fundamentals, including appropriate metrics, baselines, separation of training and evaluation data, error analysis, and reproducible experimentation.
Experience with Docker and familiarity with Kubernetes.
Familiarity with version control, software testing, and collaborative development practices.
Ability to explain technical decisions, work with people across disciplines, and learn unfamiliar tools and problem domains.
Designing task-specific evals, evaluation datasets, automated graders, or frameworks for comparing model and agent performance.
Building reinforcement learning environments, agent tools, reward functions, or verifiers.
Working with model fine-tuning, reinforcement learning, or learning from human feedback.
Developing effective ML systems with limited data, including data curation, augmentation, and synthetic data generation.
Deploying and troubleshooting Kubernetes workloads and distributed job execution.
Building systems for experiment tracking and versioning datasets, models, environments, and evaluations.
Developing backend services, APIs, databases, and interfaces for reviewing AI outputs.
Implementing systems involving sensitive data, audit trails, or structured human oversight.
Taking a technical project from initial requirements through implementation, evaluation, and deployment.
ADDITIONAL REQUIREMENTS
Willing to work extended hours and weekends as needed
COMPENSATION AND BENEFITS
Pay Range
- Level 1: $125,000.00 - $160,000.00
- Level 2: $145,000.00 - $195,000.00
Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.
Base salary is just one part of your total rewards package at SpaceX. You may also be eligible for long-term incentives, in the form of company stock or long-term cash awards, as well as potential discretionary bonuses and the ability to purchase additional stock at a discount through an Employee Stock Purchase Plan. You will also receive access to comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short and long-term disability insurance, life insurance, paid parental leave, and various other discounts and perks. You may also accrue 3 weeks of paid vacation and will be eligible for 10 or more paid holidays per year. Employees accrue paid sick leave pursuant to Company policy which satisfies or exceeds the accrual, carryover, and use requirements of the law.
ITAR REQUIREMENTS
To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.
SpaceX is an Equal Opportunity Employer; employment with SpaceX is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.
Applicants wishing to view a copy of SpaceX’s Affirmative Action Plan for veterans and individuals with disabilities, or applicants requiring reasonable accommodation to the application/interview process should reach out to EEOCompliance@spacex.com.
