SeniorStaff Software Engineer Machine Learning & System Optimization
Job Location:
Boston, NH - USA
Yearly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence.
As a Machine Learning and System Optimization Engineer you will orchestrate and allocate overall system capacity to various core perception models running on-bot as well as drive large initiatives that allow for more efficient inference by sharing various parts of the perception stack with one another.
You will focus on bringing highly efficient production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience compressing accelerating and deploying complex models including LLMs VLMs or foundation models for power- and thermal-constrained vehicle SoCs.
In addition you will optimize ML models write custom CUDA kernels and build highly concurrent inference code to ensure real-time deterministic execution on edge devices.
Allocate and distribute system resources (CPU/GPU/interconnect) to various models and inference engines running on the robot.
Spearhead cross-cutting initiatives that allow for better compute utilization through sharing/fusing models and better scheduling strategies.
Optimize large-scale models (Multi-Modal Sensor Fusion models LLMs VLMs) using advanced quantization (PTQ QAT) pruning mixed-precision inference frameworks and parameter-efficient fine-tuning (LoRA QLoRA).
Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment.
Write production-level low-latency and memory-safe C and CUDA code for real-time inference on vehicle systems.
Deep experience in system and performance optimization in CPU/GPU systems designed for low latency or high throughput.
Deep expertise in working with real-time systems & required constraints such as processing latency memory utilization and memory bandwidth pressure.
Deep expertise in model quantization (PTQ QAT) and mixed-precision inference frameworks (INT8 FP8 FP4 BF16/FP16).
Proficiency in low-level programming for AI accelerators specifically developing and optimizing custom ML OPs and TensorRT Plugins with efficient CUDA kernel implementations.
Production-level C (14/17/20) and Python programming skills with experience developing concurrent memory-safe real-time inference code for edge devices.
Prior experience in high-performance robotics applications such as AV/drones/robots.
Familiarity with SOTA autonomous driving perception algorithms (temporal 3D object detection BEV 3D Occupancy Networks) and multi-modal sensor processing (Vision LiDAR Radar).
Experience with end-to-end autonomous driving paradigms (VLM/VLA models Foundation models) and edge deployment technologies (e.g. TensorRT-LLM).
Required Experience:
Staff IC
About Company
We’re reinventing personal transportation—making the future safer, cleaner, and more enjoyable for everyone. This is on-demand autonomous ride-hailing.
