Data Scientist (Computer Vision and GenAI) at Continental

Vila Nova de Famalicão, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

21 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Vision, Generative AI, Data Science, Python, Deep Learning, CNNs, Vision Transformers, Object Detection, NLP, Cloud Platforms, Git, Model Evaluation, Data Labeling, Synthetic Data Generation, Prompt Engineering, Communication Skills

Industry

Motor Vehicle Manufacturing

Description

Company Description Continental develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the technology company offers safe, efficient, intelligent and affordable solutions for vehicles, machines, traffic and transportation. In 2024, Continental generated sales of €39.7 billion and currently employs around 190,000 people in 55 countries and markets. Job Description At Continental Tires, we aim to make analytical excellence and cutting-edge AI capabilities an integral part of all processes that drive business value. In close collaboration with our domain experts across business units, we identify complex challenges that can be addressed through advanced methods in Artificial Intelligence, with a strong focus on Large Language Models (LLMs) and Computer Vision. Leveraging these technologies enables us to extract deeper insights, adapt to rapid changes, and mitigate risks in an ever-evolving economy. As a Data Scientist specializing in LLMs and Computer Vision, you will join a global team of experts delivering innovative AI solutions and data-driven products across the tire business. Our Data Science Hub in Portugal plays a key role in this mission, fostering collaboration and excellence in state-of-the-art AI applications. Main Responsibilities: Be an integral part of projects in an area of specialization like Computer Vision and Generative AI. Help set data science standards and compliance that steers all AI based projects at Tires. Work with domain experts to understand their problems and solve them with data. Understand the Continental Tires data landscape with its diverse applications and architectures. Be a partner in connecting the necessary experts from business and IT to solve problems. Get involved in different tasks at once and involve yourself with our team to get the support you need. Support in shaping the processes and organization to leverage the business value Data Science can bring to our enterprise. Qualifications Bachelor’s degree in Computer Science, Data Science or similar studies. Minimum 2 years of IT or Industry working experience. Profound expertise in programming Data Science use cases with a widespread programming language from the community (preferably Python). Sound knowledge of code version control (e.g. Git) and code best practices. Experience with deep learning frameworks (preferably PyTorch) Experience with CNNs, Vision Transformers (ViTs), and object detection/segmentation models (e.g., YOLO, Mask R-CNN). Experience with transformer architectures (e.g., BERT, GPT, LLaMA). Knowledge of prompt engineering, fine-tuning, and model evaluation for NLP tasks. Experience with large-scale datasets, data labeling, and synthetic data generation for vision tasks. Good knowledge of cloud platforms (AWS or Azure) Very good communication skills. Proficient English language skills (written and spoken). Additional Information Our offer: Integration in a challenging and international work environment; Flexible working model; Agile and collaborative working style; Continuous opportunities for the promotion of talent and training. Ready to drive with Continental? Take the first step and fill in the online application.

Responsibilities

As a Data Scientist, you will work on projects related to Computer Vision and Generative AI, collaborating with domain experts to solve complex challenges. You will also help establish data science standards and support the integration of AI into business processes.