Lead Vision ML Engineer – Automotive Perception

Aptiv PLC; Kraków; On-site; PLN 180,000 - 280,000; Full time

Benefits offered by this job

Hybrid work

Private health care

Well-Being Program

Pension plan

Multisport card

Job summary

Aptiv Kraków is seeking a skilled ML engineer to design, train and optimize state-of-the-art models for camera-based perception, applying transformers, vision transformers, CNNs and representation learning to improve safety and reliability in automotive sensing.

You will collaborate with software and validation teams across an international organization, maintain production-quality code in Python, and contribute to software quality, testing and documentation while working in a hybrid setup.

Qualifications

• Master's degree or higher in computer science or a related field.
• Strong foundations in linear algebra, probability, and optimization.
• Proficient in Python with production-quality coding practices.
• Commitment to software quality, testing, and documentation.
• Strong analytical and problem-solving abilities.
• Fluent written and spoken English.

Responsibilities

• Design, train, evaluate, and optimize ML models for camera-based perception.
• Apply transformers, vision transformers, CNNs, and representation learning.
• Improve model performance, robustness, and inference latency.
• Collaborate with software, systems, validation, and AI/ML teams.
• Share knowledge to strengthen engineering excellence.

Skills

Python programming

Analytical thinking

Problem solving

Communication skills

English proficiency

Education

Master's degree in computer science or related field

Tools

Git

CI/CD

Agile methodologies

Rust

Job description

Aptiv Kraków is seeking a skilled ML engineer to design, train and optimize state-of-the-art models for camera-based perception, applying transformers, vision transformers, CNNs and representation learning to improve safety and reliability in automotive sensing.

You will collaborate with software and validation teams across an international organization, maintain production-quality code in Python, and contribute to software quality, testing and documentation while working in a hybrid setup.