Software Engineer, Edge AI Systems & LLM Deployment
Overview
4-10 years of software engineering experience comes alive as you own the full lifecycle of training, evaluating, and deploying LLM agents to edge hardware that interfaces with sensors and effectors. You will join a newly-formed team under The Tilted Circle LLC in Seattle, WA, working in a hybrid setup. Your stack includes Python, C++, and PyTorch, with deployment targets on NVIDIA Jetson and other hardware-constrained devices. This role stands apart by letting you shape the architecture from day one, collaborating with domain experts to solve real-time inference challenges at the tactical edge.
What You'll Do9
- 1Design and build the training pipeline for LLM agents using PyTorch and Hugging Face Transformers, targeting edge deployment.
- 2Ship Python-based microservices that interface with sensor data streams and control effectors on NVIDIA Jetson devices.
- 3Optimize inference latency and power consumption by applying quantization, pruning, and TensorRT optimization to deployed models.
- 4Lead the integration of ONNX runtime and CUDA kernels for high-performance edge inference.
- 5Debug and profile memory-constrained systems, tuning memory allocation and garbage collection for real-time reliability.
- 6Drive the continuous evaluation of edge agent performance using MLflow and Weights & Biases, iterating on model accuracy
- 7Own the deployment automation with Docker and Kubernetes (K3s) for fleets of edge devices.
- 8Collaborate with firmware engineers to define the gRPC interfaces between LLM agents and hardware controllers.
- 9Scale the system from proof-of-concept to production, handling multi-device synchronization and over-the-air updates.
Requirements8
- 14+ years of software engineering experience with a track record of building production systems.
- 22+ years of hands-on experience in LLM fine-tuning and deployment, using Hugging Face Transformers.
- 3Proven expertise in Python and C++ with deep knowledge of performance optimization for edge hardware.
- 41+ years of experience deploying models with PyTorch and TensorRT on NVIDIA Jetson platforms.
- 5Strong understanding of REST APIs, gRPC, and Docker containerization for edge services.
- 6Familiarity with Kubernetes (specifically K3s) for managing distributed edge nodes.
- 7Experience with sensor data ingestion (e.g., ROS, MQTT) and real-time control systems.
- 8B.S. or higher in Computer Science, Electrical Engineering, or equivalent practical experience.
Salary Insight
Salary not disclosed in listing
Location
Required Skills
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