Manufacturing Design Engineer Intern

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders, soldiers in battlefield scenarios and beyond.

About the role:
As a Summer 2026 Manufacturing Systems Engineering Intern you’ll focus on the systems, data, and analytics that make production run: building and operating data pipelines, integrating MES and shop-floor data sources, and delivering operator-facing dashboards and analytic products that drive decisions across production, quality, and supply chain. You’ll partner with manufacturing, quality, and software teams to translate shop-floor questions into reliable data products that surface root causes, monitor process health, and enable faster, more predictable production ramp.

How you'll make an impact (example projects below):

Below are representative projects you may own. Each is an opportunity to turn raw production data into reliable insights that scale to full production.

• Integrate MES / shop-floor data into a central analytics platform
Deliverables: integration plan (sources, schemas, cadence), ETL/ELT pipelines ingesting MES / PLC / test-stand data into Databricks (or equivalent), automated data quality checks, and documented data model.

• Build near real-time production dashboards for operators and supervisors
Deliverables: high-level and station-level dashboards (Looker/Tableau/PowerBI or embedded web dashboards) showing KPIs (OEE, yield, cycle time, WIP, rejects), drill-downs to failed units, and operator-facing views. Include mockups, implementation notes, and a rollout plan.

• Automate KPI calculations & alerts (OEE, first-pass yield, SPC)
Deliverables: production-grade Databricks notebooks or jobs that calculate KPI time-series, SPC charts, automated anomaly detection/alerts, and unit-level traceability to identify defect clusters.

• Build & validate dashboards for pilot builds and line expansion
Deliverables: pilot build dashboards, rollout checklist, performance baselines, and documented validation showing that dashboards accurately reflect pilot outcomes.

What makes you a good fit

You’ll thrive if you have a mix of data engineering, analytics, and a practical understanding of manufacturing. Examples of what we look for:

• Currently pursuing a degree in Industrial Engineering, Manufacturing Engineering, Computer Science, Data Science, Electrical Engineering, or a related technical field.

• Hands-on experience with SQL and Python — comfortable writing production queries and notebooks.

• Familiarity with cloud analytics / data platforms (Databricks / Spark, Delta Lake, or similar).

• Understanding of MES concepts and shop-floor data (OEE, takt time, cycle time, yield) and how to map MES signals to production events.

• Basic data engineering skills: data modeling, time-series handling, data quality tests and monitoring.

• Ability to work on the factory floor to gather requirements and validate dashboards / data (comfortable in a production environment).

• Good communicator: able to partner across manufacturing, quality, supply chain, and software teams to define metrics and interpret results.

• Strong problem solver: can take ambiguous manufacturing questions and produce reproducible data products and analyses.

• Attention to detail and a documentation mindset: data contracts, lineage, and reproducible notebooks that others can run.

Nice to have (not required):

• Databricks / Spark production experience, experience with MES systems (Siemens Opcenter, Tulip, etc.)

• Previous experience as an intern in a production environment.

Compensation Range: The hourly base salary range for this position is $47/hr for Undergrad, $53/hr for Graduate students, and $58 for PhD students*. Compensation will vary based on factors, including skill level, proficiencies, transferable knowledge, and experience. In addition to base salary, Skydio full-time employees are eligible to enroll in our benefit plans and take advantage of a variety of incentives and stipends.

*For some positions the pay may be dependent upon the individual's regional location.

#LI-ZD1

At Skydio we believe that diversity drives innovation. We have created a multidisciplinary environment that embraces the power of diverse perspectives to create elegant solutions for complex problems. We are committed to growing our network of people, programs, and resources to nurture an inclusive culture.

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or other characteristics protected by federal, state or local anti-discrimination laws.

For positions located in the United States of America, Skydio, Inc. uses E-Verify to confirm employment eligibility. To learn more about E-Verify, including your rights and responsibilities, please visit https://www.e-verify.gov/