BA
BarcoDevOps Engineer
DevOps Engineer enabling R&D team with software creation and operational automation. Defining CI/CD pipelines and implementing devSecOps practices.
About the role
- Lead the end-to-end deployment of deep learning models into production, ensuring they are fast, scalable, and reliable
- Optimize neural network inference on GPUs, embedded devices, and edge systems
- Develop production-grade software that meets the highest standards for robustness, latency, and maintainability
- Collaborate closely with research teams, data scientists, and software engineers to translate experimental models into real-world applications
- Mentor junior engineers and share your deep expertise across the team, shaping best practices for DL deployment
- Evaluate new tools, frameworks, and technologies to push the boundaries of AI deployment
Requirements
- 10+ years of experience in AI, deep learning, or related fields
- Strong expertise in neural network inference, model optimization, and performance tuning
- Proficiency in C++ and Python
- Deep knowledge of CUDA, GPU programming, TensorRT, and ONNX Runtime
- Solid experience with embedded systems and production-grade software
- A problem-solving mindset, attention to detail, and a drive to make AI work at scale
Benefits
- Worklife Mode: Design your own work setup, balancing focus and flexibility
- Tech in Action: Be the person who ensures that world-class AI models actually run in production
- Collaborative culture: Work alongside talented, driven individuals in a low-ego environment
- Freedom to grow: Shape your career path and influence the technical direction of the company
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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