Full-Stack Data Scientist, Hardware Reliability

SpaceX

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Bastrop, TX
Posted: 54 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Similar $172k

$121k $212k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $141,537–$202,925.

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About SpaceX

SpaceX designs, manufactures, and launches advanced rockets and spacecraft with the mission of enabling humans to become a multi-planetary species. It operates the Falcon 9, Falcon Heavy, and Starship launch vehicles, as well as the Starlink satellite internet constellation.

SpaceX currently has 851 open roles on FindRole.

Listed pay typically runs $130,000–$165,000 across 590 roles with salary data.

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TL;DR · Full-Stack Data Scientist, Hardware Reliability

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Full-Stack Data Scientist, Hardware Reliability (Starlink) As a Full-Stack Data Scientist on the Starlink Reliability team, you will build data pipelines, models, and production scoring systems to improve the reliability of customer hardware, including dishes, routers, and power supplies. You will develop models to predict hardware failures using telemetry, manufacturing, inventory, and unstructured support data like tickets and images. Your daily work involves training, validating, and deploying models into production, building internal analytics tools, and creating LLM-backed tools featuring retrieval, tool calling, and agentic workflows. You must possess strong proficiency in Python and SQL, with experience in machine learning production, data pipeline orchestration, and large-scale data processing. This role solves technical reliability problems by turning data into design and process changes for the global satellite broadband network.

Skills

Python SQL Machine Learning Data Pipelines LLM RAG Relational Databases Data Visualization Go Java C++ C# Statistical Analysis Survival Analysis System Design Data Structures Algorithms

What you'll do

Build and maintain data pipelines and infrastructure to improve Starlink hardware reliability.
Design and operate feature, label, and scoring data for reliability model training.
Train, validate, and iterate models for hardware failure prediction in production and the field.
Deploy and monitor production models, including scheduled scoring and versioning.
Contribute to core internal and customer-facing software repositories.
Build internal analytics tools, APIs, and applications for hardware and supply chain teams.
Develop LLM-backed tools featuring retrieval, tool calling, and agentic workflows.
Extract signals from unstructured data like support tickets, chats, and images.

What we're looking for

Bachelor’s degree in computer science, data science, mathematics, electrical engineering, or other STEM discipline.
4+ years of professional experience in data science, machine learning, or software engineering.
Strong proficiency in Python and SQL.
Experience building production data pipelines.
Experience deploying machine learning models in production.
Master’s degree in computer science, data science, mathematics, or other STEM discipline (or PhD with 3+ years of relevant experience) (preferred).
Strong understanding of software engineering fundamentals including data structures, algorithms, system design, and concurrency (preferred).
Experience shipping large language models in production, including RAG, tool calling, and agentic workflows (preferred).
Must be a U.S. citizen, national, lawful permanent resident, refugee, asylee, or eligible for required Department of State authorizations.

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