Founding Textile Engineer for AI-Driven Manufacturing

Nextex AI; Delaware; Hybrid; USD 34,000 - 43,000; Full time

Benefits offered by this job

Founding team

Equity up to 15%

EXIST grant €2,500/month

Health insurance

Leadership path

Berlin ecosystem access

Pilot factories access

Collaboration with manufacturers

Gym membership support

Flexible working

High ownership

Industrial AI impact

Job summary

NexTex AI seeks a Founding Textile Engineer to bridge textile manufacturing expertise with AI-based production intelligence. You will collaborate with our AI team, pilot factories, and machine partners to translate textile knowledge into scalable AI solutions across knitting, dyeing, finishing, and quality control.

You will focus on knitted fabrics, defect taxonomy, and process improvements, working closely with production teams to define standards, datasets, and KPIs for textile quality and

Qualifications

• Degree in Textile Engineering, Textile Technology, or related field.
• Strong understanding of knitted fabrics and circular knitting.
• Experience identifying textile defects and production issues; knowledge of ΔE and dyehouse quality.

Responsibilities

• Work with knitting, dyeing, finishing, and quality control in textile production environments.
• Identify, classify, and document textile defects and production anomalies.
• Analyze root causes of production issues and support corrective actions.
• Collaborate with AI engineers to translate textile challenges into ML/CV applications.

Skills

Fluent English

Analytical thinking

Problem solving

Independent

Team communication

Education

Degree in Textile Engineering / related

Job description

NexTex AI seeks a Founding Textile Engineer to bridge textile manufacturing expertise with AI-based production intelligence. You will collaborate with our AI team, pilot factories, and machine partners to translate textile knowledge into scalable AI solutions across knitting, dyeing, finishing, and quality control.

You will focus on knitted fabrics, defect taxonomy, and process improvements, working closely with production teams to define standards, datasets, and KPIs for textile quality and