Sr. Edge Compute Software Engineer
Role details
Job location
Tech stack
Job description
You will contribute to the development, integration, and optimization of Loft's Ultimate Edge SDK, which provides unified compute capabilities across various embedded platforms. Your primary focus will be on NVIDIA Orin-based systems, while also assessing portability and performance on additional hardware targets. Your mission will include:
- Integrating ONNX-based inference runtimes and image-processing frameworks (e.g., ONNX Runtime, OpenCV) into Loft's SDK.
- Configuring and optimizing GPU-accelerated and heterogeneous runtime environments, ensuring efficient use of available resources.
- Profiling, benchmarking, and performance tuning across multiple embedded platforms.
- Collaborating with other teams in Loft to ensure smooth deployment of edge applications.
- Supporting the continuous improvement of Loft's onboard compute stack through structured testing, documentation, and validation.
Your work will directly contribute to flight software robustness, system performance, and future onboard computing capabilities for Loft missions., + Integrate and optimize runtime components (ONNX Runtime, OpenCV, etc.) within the Ultimate Edge SDK.
- Develop, configure, and tune GPU-accelerated pipelines on NVIDIA hardware.
- Benchmark and profile workloads to assess performance, portability, and resource usage.
- Support application deployment in real-time, embedded, and constrained environments.
- Contribute to documentation, validation, and continuous integration of runtime components.
Requirements
Do you have experience in Slack?, Do you have a Master's degree?, + Master-level background in embedded systems, computer engineering, AI/ML, or software engineering.
- Solid experience with C++ and/or Python.
- Familiarity with Linux-based embedded environments.
- Understanding of ML inference frameworks (ONNX Runtime, TensorRT, etc.).
- Strong experience with containerization technologies (e.g., Docker, Kubernetes) and exposing processing capabilities or services from containerized workloads
- Experience with hardware-accelerated processing (e.g., GPUs, TPU...) to optimize performance for compute-intensive workloads.
- English communication skills (written & verbal) for international collaboration., + Experience with the NVIDIA ecosystem: CUDA, Orin, Jetson platforms.
- Knowledge of heterogeneous compute environments and optimization.
- Exposure to runtime systems, GPU scheduling, or edge computing.
- Interest in space technologies and autonomous onboard processing.
Benefits & conditions
- Equity, we want you to have an active role in our success
- Up to 35 days of Paid Time Off (vacations & RTT ) and flexible working hours, we want you to be at your best
- Health and life insurance, we care about your health
- Lunch Vouchers, because let's be honest, we love food! (we even have a slack channel about it #loft-gourmand)
- Cross-office travel opportunities between San Francisco, Colorado, and Toulouse to learn from our differences
- Company and team off-sites and many other events to work & celebrate together