Lead AI Engineer

Lead AI Engineer

Must Have

• Education: Master or PhD degree in Computer Science, Software Engineering, or a related field
• Experience:
• 10+ years of experience as an AI Engineer, Machine Learning Engineer, Software Engineer, Data Scientist, or a related role
• Proven experience delivering AI solutions from concept and prototyping through industrialization and production deployment
• Experience leading technical initiatives and coordinating cross-functional engineering activities
• Experience translating business and product requirements into implementation plans and technical solutions
• Experience working across multiple AI domains such as computer vision, generative AI, large language models (LLMs), machine learning, or industrial AI
• Experience collaborating with software engineering, systems engineering, product, and customer-facing teams
• Experience mentoring engineers and providing technical guidance within development teams
• Skills
• Strong programming skills, especially in Python
• Strong understanding of software engineering, machine learning, and AI solution development
• Experience with AI frameworks such as PyTorch, TensorFlow, OpenCV, Hugging Face, LangChain, or similar technologies
• Experience designing and delivering production-grade AI systems and applications
• Understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and modern AI architectures
• Good understanding of software architecture, system integration, cloud and edge deployment concepts
• Experience reviewing software designs, code quality, and engineering best practices
• Strong analytical, problem-solving, and decision-making skills
• Leadership
• Ability to provide technical leadership and coordinate engineering activities across multiple disciplines
• Ability to break down complex objectives into actionable work packages and priorities
• Ability to drive execution while balancing innovation, quality, and delivery timelines
• Strong mentoring and coaching capabilities
• Communication: good verbal communication skills, with the ability to convey complex concepts.

Preferred attribute

• Visionary and innovative: ability to act pro-actively and creatively and propose groundbreaking solutions, curiosity for new technologies.
• Pragmatic: focus on solutions to be implemented in serial and industrialized products.
• Adaptable: comfortable working in a fast-paced, dynamic environment.
• Collaborative: Enjoys working across disciplines, functions, and international teams
• Business-oriented: Understands how AI can address customer challenges and deliver measurable impact

Your tasks

• Lead the technical execution of AI initiatives and provide day-to-day technical leadership across AI projects
• Translate business, product, and customer requirements into implementation plans and technical work packages
• Coordinate activities across AI Data Scientists, AI Engineers, AI Data Engineers, and AI Systems Engineers
• Drive the design, development, evaluation, deployment, and industrialization of AI solutions
• Review solution designs, software architecture, implementation approaches, and code quality
• Establish and promote engineering best practices, technical standards, and development processes
• Resolve technical dependencies, implementation challenges, and cross-functional integration issues
• Collaborate closely with software, systems, product, and engineering teams to integrate AI capabilities into products and digital platforms
• Support architectural decision-making and ensure consistency across AI solutions
• Mentor engineers and provide technical guidance across the AI organization
• Facilitate technical alignment meetings, design reviews, and technical knowledge sharing
• Identify technical risks and escalate strategic decisions and critical issues when necessary
• Support innovation initiatives, customer engagements, and pre-sales activities when required

Interested in shaping the future of textile quality assurance?
Apply now and join our mission to deliver excellence in every thread.

Selection process:

1st round: Online technical assessment

2nd round: Interview via Teams

3rd round: HR discussion