Senior Computer Vision Engineer
vor 2 Wochen
Company Description
AUTO1 Group is Europe's leading digital automotive platform. Within AUTO1, our dedicated Computer Vision team is at the forefront of innovation, building the next generation of technology for the used car market. Our mission is to create a new, objective standard for vehicle assessment. We develop and deploy proprietary devices that automatically inspect used cars for exterior damages like scratches, dents, and other imperfections, bringing unprecedented transparency and efficiency to the industry. We are a focused, engineering-driven team building complex, real-world systems that merge hardware, software, and deep learning.
The Role
We are looking for an experienced and pragmatic Senior Computer Vision Engineer to take ownership of key components of our production computer vision pipeline. This is a hands-on role for an engineer who thrives on solving complex challenges and is passionate about building robust, reliable systems.
You will be responsible for maintaining, optimizing, and evolving the sophisticated models that power our inspection devices. You will also play a crucial role in our data engine, working directly with our in-house annotation team to ensure the highest quality data fuels our models. As we grow, you will help lead the charge on new projects, adapting our proven technology and developing new solutions to expand our capabilities.
Job Description
What You'll Do
- Maintain, optimize, and ensure the reliability of our complex, multi-stage computer vision pipeline, which includes models for semantic segmentation, object detection, image classification, and optical flow estimation.
- Set the technical vision and roadmap for specific parts of the CV pipeline, making key architectural and algorithmic decisions to drive performance and accuracy.
- Lead the adaptation of existing models and the development of new components for upcoming projects, translating business needs into technical solutions.
- Oversee the entire data lifecycle for your models, from defining clear annotation guidelines to managing data quality and iterating on the feedback loop with our in-house annotation team.
- Write clean, maintainable, and robust production-level Python code, adhering to strong software engineering best practices.
- Manage model training, experimentation, and evaluation on our on-premise Linux server infrastructure.
Qualifications
- Master's degree or PhD in Computer Science, or a related field.
- 5+ years of professional experience building and deploying computer vision models in a production environment.
- Deep, hands-on expertise with PyTorch.
- Proven experience across a range of computer vision tasks (e.g., object detection, semantic segmentation, image classification).
- Exceptional software engineering fundamentals with a focus on writing clean, testable, and efficient Python code.
- High proficiency in a Linux environment is mandatory. You should be comfortable and efficient using shell scripting, SSH, and command-line interfaces for daily work.
- Demonstrated experience working with data annotation pipelines, defining guidelines, and ensuring data quality.
- Excellent problem-solving skills and the ability to work independently and take ownership of projects.
- Willingness to embrace new ideas and feedback, work collaboratively with others, and continuously seek improvement.
Nice-to-Haves
- Experience working with large-scale datasets (TBs) and building efficient data processing pipelines.
- Experience with model optimization techniques (e.g., quantization, pruning, TensorRT/ONNX conversion).
- Experience mentoring junior engineers or providing technical leadership.
Our Tech Stack
Primary Framework: PyTorch
Infrastructure: In-house Linux servers, CLI, SSH
Annotation: In-house custom tooling
Additional Information
Contact
Igor Popov
At AUTO1 Group we live an open culture, believe in direct communication, and value diversity. We welcome every applicant; regardless of gender, ethnic origin, religion, age, sexual identity, disability, or any other non-merit factor.
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