Tesla

Makes electric cars, robotaxis and grid batteries

Process Engineer - Cell Formation

Process EngineeringConfirmed live in the last 24 hours

Full-timeAustin, TX, USANo salary listedIn-person

About the Job

Requirements

A degree in Chemical Engineering, Materials Science, Industrial Engineering, Mechanical Engineering, Electrical Engineering, Physics, Statistics, Computer Science, Data Engineering, or equivalent experience is required.
Working knowledge of Python and SQL for data analysis is required.
Strong data analysis skills, including time-series and manufacturing performance data, statistics, and data-driven root-cause problem solving, are required.
Ability to interpret high-volume manufacturing process data, design or support experiments, and turn findings into clear recommendations with measurable impact is required.
Ability to translate process needs into data problems and data findings into actions the factory can run is required.

Responsibilities

Analyze Formation yield daily to separate measurement or calculation errors from true quality shifts in upstream material, process, or equipment, and drive the appropriate action.
Analyze key Formation metrics for process, material, and equipment changes to confirm there is no quality risk, and lead data-driven change approvals.
Analyze equipment capacity and throughput to identify bottlenecks and support process decisions that maximize output without sacrificing quality.
Develop an understanding of Cell-Formation factory process flows to identify and address anomalies, and of Formation fundamentals to explain metric shifts and their impact on cell quality.
Build an understanding of key battery pack analytics to challenge limits and optimize for cell yield and quality; support adoption of testing protocols and process limits into production.
Partner with Cell Quality, Reliability, Materials, and Battery teams to balance yield, quality, and throughput under changing volume constraints.
Use Python, SQL, and data pipelines to maintain trustworthy Formation metrics; create visualizations, dashboards, and reports using Tableau, Grafana, or similar tools to monitor KPIs and support decision-making.
Apply statistics, automation, and AI-assisted workflows to speed quality investigations and generate preliminary root-cause analysis for engineering review.

Desired Qualifications

Familiarity with dashboards and data pipelines is a plus.

Category	Manufacturing
Location	AUSTIN, Texas
Requisition ID	287496
Type	Full-time

Job Description

<p>We are seeking an engineer to sit between Cell Formation process and production, using data to make faster, better factory decisions. This role focuses on identifying and applying a Formation strategy that delivers maximum cell quality and performance at minimum factory cost, cycle time, and equipment capacity. You will own the metrics and analyses that explain yield and quality on the floor, evaluate tradeoffs between formation duration, throughput, and cell COGS (yield and warranty), and help deploy the right process decisions against moving capacity and volume-ramp constraints — reducing formation cost and time while protecting world-class quality.</p>

Job Responsibilities

Analyze Formation yield daily to separate measurement or calculation errors from true quality shifts in upstream material, process, or equipment — and drive the right action
Analyze key Formation metrics for process, material, and equipment changes to confirm there is no quality risk, and lead data-driven change approvals
Analyze equipment capacity and throughput to identify bottlenecks and support process decisions that maximize output without sacrificing quality
Develop a strong understanding of Cell-Formation factory process flows to identify and address anomalies, and of Formation fundamentals so you can explain metric shifts and their impact on cell quality
Build an understanding of key battery pack analytics to challenge limits and optimize for cell yield and quality; support adoption of testing protocols and process limits into production
Partner with Cell Quality, Reliability, Materials, and Battery teams to balance yield, quality, and throughput under changing volume constraints
Use Python, SQL, and data pipelines to keep Formation metrics trustworthy; create visualizations, dashboards, and reports (Tableau, Grafana, or similar) to monitor KPIs and support decision-making
Apply statistics, automation, and AI-assisted workflows to speed quality investigations and generate preliminary root-cause analysis for engineering review

Job Requirements

Degree in Chemical Engineering, Materials Science, Industrial Engineering, Mechanical/Electrical Engineering, Physics, Statistics, Computer Science, Data Engineering, or equivalent experience
Working knowledge of Python and SQL for data analysis; familiarity with dashboards and data pipelines a plus
Strong data analysis skills, including time-series and manufacturing performance data, statistics, and data-driven root-cause problem solving
Ability to interpret high-volume manufacturing process data, design or support experiments, and turn findings into clear recommendations with measurable impact
Strong communication skills: translate process needs into data problems, and data findings into actions the factory can run

About the Company

Tesla

Makes electric cars, robotaxis and grid batteries

Tesla makes electric cars and batteries that store power for homes and utilities, and it develops self-driving software and humanoid robots. In 2023, its Model Y became the first electric vehicle to rank as the world's best-selling car. Buyers order the Model 3 sedan, Model Y SUV, or Cybertruck pickup directly from Tesla instead of through dealers, and they charge on its Supercharger fast-charging network. It also sells Megapack and Powerwall batteries, runs a robotaxi service, and charges drivers a monthly fee for self-driving software that still needs their supervision. Tesla was founded in 2003, with Elon Musk as its lead early investor and a recognized co-founder, and it is based in Austin, Texas.

Company size: 10,001+
Company stage: IPO
Headquarters: Austin, TX
Founded: 2003

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