A on-site Data & ML role at Anduril Industries.
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Original listing text, shown exactly as published by the company.
This is a builder role. You will own end-to-end data and analytics work that shows up directly on a factory floor. You'll pull data from real production systems (ERP, MES, QMS, Inventory), shape the data into pipelines and ontologies in Palantir Foundry and Databricks, and partner with engineers, ML practitioners, and program quality leads to ship analytics products people actually use.
You will be expected to use AI aggressively in your own work to draft pipelines, write tests, generate dashboards, explore unfamiliar data, and accelerate the repetitive parts of the job.
You will also be expected to be near the hardware. Manufacturing is a building full of people who need answers from your data, and the best engineers on this team are the ones who walk the line, ask "what is this part," and let that shape the schema.
Investigate Data Quality: Act as a lead technical investigator for data quality issues. When a dashboard is inaccurate or data seems wrong, you will perform deep-dive analysis using SQL and Python to trace the problem back to its source and identify the root cause.
Troubleshoot & Optimize: Support the analytics team by troubleshooting data access issues, improving pipeline performance for faster dashboard loads, and ensuring the overall health and reliability of the quality data ecosystem in Foundry.
Drive Technical Improvements: Implement robust data quality checks, validation rules, and automated monitoring directly within data pipelines to proactively prevent future data quality issues and eliminate variance.
Enable Self-Service Analytics: Partner closely with cross-functional teams and ML Engineers to understand current and future data needs. Build clean, reliable, and well-structured datasets that allow teams to independently create reliable dashboards, reports, and models.
Lead Data Projects: Collaborate with partner teams on analytics initiatives from requirements gathering through deployment. Explore efficient ways to deliver the ask, partnering with Data Scientists and other analysts to deliver high-impact, well-rounded solutions.
Build AI-Assisted Tools: Develop small apps and workflows (often in Foundry Workshop / AIP) that reduce repetitive analyst work by 10x, leveraging operations knowledge gained directly from conversations with your stakeholders.
Capability Discovery: Partner with program quality leads who don't yet know what Quality Intelligence can do for them. Translate their operational problems into data products that already exist or can be configured quickly.
Hands-on & Curious: You are comfortable on the factory floor. You'd rather spend an hour with a manufacturing engineer reviewing a part than guess at column names from your desk.
Impact-Driven: You measure your work by what ships and gets used. You'd rather own a small set of pipelines that operators depend on than a wide backlog that no one is asking for.
Technical & Pragmatic: You write SQL and Python regularly and readily understand code generated by AI. You can read another engineer's pipeline, identify weaknesses, and suggest concrete improvements.
Clear Communicator: You communicate plainly. You can explain a complex data anomaly to a director without jargon, and to an engineer without losing precision.
3+ years in a hands-on data role: Data Engineer, Analytics Engineer, BI Engineer, or similar.
Production experience with Foundry, Databricks, Snowflake + dbt, or an equivalent cloud lakehouse—you have built and maintained pipelines that other teams depend on.
Strong SQL skills on large, multi-source datasets (joins across heterogeneous systems, window functions, and performance tuning).
Strong Python skills for data transformation and scripting (Pandas, PySpark, or equivalent).
Demonstrated ability to perform root-cause analysis on complex data issues—when a number looks wrong, you can trace it back through the stack and explain why.
Comfort using AI coding tools in your daily workflow, with a clear view of where they help and where they don't.
Willingness to work in and around manufacturing operations, including periodic time on the production floor and at remote sites.
Strong cross-functional communication skills, with the ability to hold substantive conversations with engineers, non-technical operators, and program leadership.
Must be a U.S. Person (U.S. Citizen or Permanent Resident) due to ITAR/export control regulations.
Familiarity with quality methodologies: RCCA / 8D, FMEA, GD&T, IQC/OQC, control-plan design.
Defense or regulated-manufacturing experience (ITAR, AS9100, IPC-610, MIL-STD-1916, or similar).
Experience building dashboards in Foundry Workshop / Quiver / AIP, Tableau, or PowerBI, with a clear understanding of how upstream data models drive performance.
Strong software engineering practices: Git, code reviews, CI, and testing data code with the same rigor as application code.
Experience integrating LLMs or ML models into analytics workflows (e.g., RAG over operational data, AI-assisted triage, or agentic data exploration).
Comfort with standard collaboration tools: Slack, Jira, Confluence.
A DAY IN THE LIFE
10:30 AM: Pairing with a manufacturing engineer on the production floor to resolve a part the data is mis-classifying—you leave with new test cases for your pipeline.
1:00 PM: Refactoring an ontology object that has grown unwieldy, using Claude or Cursor to accelerate the change. Ship behind a feature flag.
2:30 PM: Reviewing the Piece Part Plan onboarding flow with a program quality lead and scoping how it could apply to their program.
3:30 PM: Focused work: instrumenting a new data-quality check in a Foundry pipeline to catch a class of bad-supplier rows you noticed last week.
5:00 PM: Writing a quick Confluence summary so the next person on the team does not have to relearn what you just figured out.
LOCATION & TRAVEL
Travel: ~10–20% to manufacturing and remote sites.
US Person Status: U.S. Person status is required as this position needs to access export-controlled data.
US Salary Range$144,000—$191,000 USD
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:
Anduril Industries
Data & ML
94 open roles on Sydicom
Anduril Industries, Inc. is an American military technology company specializing in the development of advanced autonomous systems. The company was founded in 2017 by Palmer Luckey, Trae Stephens, Matt Grim, Joe Chen, and Brian Schimpf. Anduril sells systems to the U.S. Department of Defense that incorporates artificial intelligence and robotics. Anduril's major products include unmanned aerial systems (UAS) and counter-UAS (CUAS), semi-portable autonomous surveillance systems, and networked command and control software. It is privately owned, and as of May 2026, the company has a valuation of $61 billion.
Source: Wikipedia
