Computer Vision Engineer

Eviden is an Atos Group business with an annual revenue of circa € 5 billion and a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 55,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come.

Our team is building Eviden Computer Vision Platform, a real-time video analytics solution for different verticals.

We use AI technologies to design and develop the product, as well as Big Data software components to manage the related data. We are seeking a skilled and motivated Computer Vision Engineer to complete our team on models’ development and generative AI.

Responsibilities:

Develop and implement Computer Vision Models using deep learning techniques.

• Software development to contribute to the development and optimisation of computer vision algorithms and features.

• Explore and implement Generative AI and Stable Diffusion models to generate synthetic datasets for models training.

• Investigate about latest trends in Computer Vision.

Education:

• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or a related field.

Essential knowledge and professional experience:

• Computer vision knowledge (2+ years of relevant experience): Deep learning , pattern recognition , linear algebra.

• Good programming skills (2+ years of experience): Python, C++

• Experience (2+years) with CV tools/libraries, e.g., OpenCV, Keras, Tensorflow, PyTorch, Pandas.

• Experienced in working with virtualized environments and containers (Docker, Kubernetes)

• Ability to work with software configuration management tools such as Git or GitLab.

• Proficient user of Linux environments.

• English level B2 Additional knowledge • Usage of Generative AI / Stable Diffusion models.

• Multimodal text and image models.

• Zero-shot learning models, e.g., Grounding DINO, CLIP, Segment Anything Model (SAM).

• Experience in MLOps tools, e.g., MLFlow, Kubeflow.

Competences:

• Fluency in English

• Good writing and presentation skills.

• Strong personal soft skills set communicative, enthusiastic, highly collaborative, proactive, and self-driven.

• Ability and enthusiasm to learn new technologies quickly.

Benefits:

• Half-day Fridays.

• Intensive workday in summer.

Let’s grow together.