Interested in this AI/ML Engineer role at SpaceXSI?
Apply Now →Skills & Technologies
About This Role
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.
ABOUT THE ROLE:
You will evaluate, refine, and create elite-level writing in a variety of genres and formats to advance Grok's capabilities in one or more Writing Specialty areas.
RESPONSIBILITIES:
- Use proprietary software to label, annotate, and refine AI-generated text for clarity, structure, engagement, and domain-specific accuracy.
- Utilize one or more Writing Specialty areas of expertise (e.g., Creative Fiction Writing, Game Writing, Technical Writing) to deliver high-quality curated data to improve Grok's writing outputs, both generally and given specific audience expectations and/or use-case requirements.
- Collaborate with engineers and other specialists to develop tasks that advance AI's writing proficiency.
- Improve annotation tools and workflows for efficiency.
- Pivot as needed to work on secondary tasks to improve Grok as needed in writing-based and non-writing-based areas.
BASIC QUALIFICATIONS:
- Proven proficiency in English and qualification for at least one chosen Writing Specialty (see below for Writing Specialty-specific qualifications).
- Ability to critique and refine AI-generated text for readability, logical flow, grammar, consistency, style, creativity, imaginative elements, and reader immersion.
- Strong attention to detail, with experience using reference materials, style guides, and resources for accurate, style-adherent annotations.
- Flawless grammar, spelling, clarity, and precision.
- Superlative communication, interpersonal, analytical, and editorial skills.
- Commitment to developing AI that produces expert-level writing.
- Highly adaptable and able to work under deadlines.
Applicants will be asked to provide verifiable proof of speciality-specific qualifications.
- Creative Fiction Writing: At least two of the following: (1) verified novel publishing deals with major houses (e.g., Big Five); (2) novel sales >50,000 units (excluding free promotions); (3) 10+ short stories in major outlets (e.g., The New Yorker, Clarkesworld); (4) major awards recognition (e.g., Hugo, Nebula finalist or comparable); (5) critical acclaim (e.g., starred reviews in Kirkus, Publishers Weekly, features in Library Journal or NY Times Book Review).
- Game Writing: All of the following: (1) 5+ years of professional game writing experience; (2) public portfolio showcasing branching narratives, character development, dialogue trees, and measurable player impact (e.g., reviews or engagement metrics); (3) published credits in notable games, demonstrating expertise in narrative design, lore creation, and integration with gameplay mechanics.
- Technical Writing: All of the following: (1) 5+ years in technical writing, focusing on user manuals, API documentation, software guides, or technical reports for tech, engineering, or scientific fields; (2) public portfolio of high-impact examples (e.g., docs that reduced support tickets by 20%+, improved user adoption metrics, enhanced compliance rates); (3) Certifications from Society for Technical Communication (STC) Certified Professional Technical Communicator (CPTC), or equivalent; (4) Bachelor's degree or higher in Technical Communication, English, Computer Science, or related field.
- Nonfiction Writing: All of the following: (1) 5+ years in non-fiction writing (memoirs, biographies, historical accounts), with 3+ published books showing commercial and/or critical success; (2) public portfolio of samples/manuscripts demonstrating structure, prose, and non-fiction standards; (3) awards, funding success, or memberships in orgs like BIO/ASJA. Bachelor's degree or higher in English, History, or Journalism highly preferred.
- Journalistic Writing: All of the following: (1) 5+ years of professional experience in journalism, reporting for reputable outlets; (2) expertise in investigative journalism, feature writing, or specialized beats; (3) public portfolio of published work with bylines in major outlets (e.g., NYT, BBC), with awards, citations, or engagement metrics; (4) Bachelor's degree or higher in Journalism, Communications, English, or related field.
- Copywriting: All of the following: (1) 5+ years in copywriting or marketing writing, with proven high-impact campaigns for brands, agencies, or in-house teams; (2) expertise across ad copy, email sequences, landing pages, and social media; (3) experience as Content Strategist, Copy Chief, or Marketing Writer; (4) public portfolio with quantified impacts (e.g., 30%+ conversion boosts, engagement/revenue growth); (5) Bachelor's or higher in Marketing, Communications, English, or related. Experience in diverse industries (e.g., tech, healthcare, finance, consumer goods, entertainment) showing adaptable tone, style, strategy (e.g., B2B tech vs. B2C retail) highly preferred.
- Web Writing: All of the following: (1) 5+ years of professional experience in web content creation, digital marketing, or related roles; (2) demonstrated SEO-optimized writing expertise with proven increases in organic traffic and engagement via content strategies; (3) experience managing full content lifecycles (research, writing, editing, and publishing); (4) public portfolio of high-impact work (e.g., viral articles, conversion-focused landing pages, B2B whitepapers with quantifiable growth); (5) certifications in digital marketing tools (e.g., Google Analytics, SEMrush); (6) Bachelor's degree or higher in Journalism, Communications, English, Marketing, or related.
- Grant Writing: All of the following: (1) 5+ years of grant writing with proven record of securing funding in excess of $1M across multiple grants and a win rate of 50% or higher; (2) expertise in researching funding opportunities and understanding grant guidelines from various sources; (3) samples of narratives, budgets, and evaluation plans that showcase persuasive writing, logical structure, and alignment with funder priorities; (4) Bachelor's degree or higher in Communications, Public Policy, Nonprofit Management, or related.
- Academic Writing: All of the following: (1) 5+ years in academic writing, with extensive experience in peer-reviewed publications, theses, dissertations, or scholarly books for academic fields; (2) authored articles in top-tier journals, books with reputable presses, citations exceeding 500+ via Google Scholar, or an h-index of 10 or higher; (3) public portfolio of samples, including abstracts, full papers, or proposals demonstrating rigorous argumentation, citation styles (APA, MLA, Chicago), and original contributions; (4) PhD in relevant field. Postdoctoral experience or fellowships (e.g., Fulbright) preferred.
- Poetry Writing: All of the following: (1) advanced degree in creative writing, literature, poetry, or related; (2) publications in reputable literary journals, anthologies, or poetry collections that demonstrate mastery of a wide range of traditional forms, from haiku to sonnet to villanelle; (3) history of awards, fellowships, or residencies from recognized organizations; (4) one or more of the following: (a) published collections with major presses, (b) poems in outlets like Poetry Magazine, (c) awards like National Book Award for Poetry, (d) fellowships from NEA or Guggenheim. Special Note: If your publication record is primarily free verse, please do not apply, as the position requires a deep understanding of classical forms and poetic techniques.
PREFERRED SKILLS AND EXPERIENCE:
- Familiarity with AI tools or prompt engineering.
- Ability to teach or critique writing in a collaborative environment on both technical and non-technical levels.
- Familiarity with Google Workspace, Slack, Notion, and other remote work and collaboration tools.
LOCATION & OTHER EXPECTATIONS:
- Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
- For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
- Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
- For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
- We are unable to provide visa sponsorship.
- For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.
COMPENSATION AND BENEFITS:
US based candidates: $35/hour - $75/hour depending on factors including subspecialty applied for, relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.
Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.
SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice*.*
Salary Context
This $72K-$156K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At SpaceXSI, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($114K) sits 46% below the category median. Disclosed range: $72K to $156K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
SpaceXSI AI Hiring
SpaceXSI has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span Remote, US, Palo Alto, CA, US. Compensation range: $156K - $440K.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.