Senior Deep Learning Inference Engineer

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch

Job Description

Cruisers have the opportunity to grow and develop while learning from leaders at the forefront of their fields. With a culture of in ternal mobility, there's an opportunity to thrive in a variety of disciplines. This is a place for dreamers and doers to succeed.

If you are looking to play a part in making a positive impact in the world by advancing the revolutionary work of self-driving cars, join us.

The AV software stack heavily relies on machine learning techniques to perform variety of tasks, each with different requirements of hardware/compute resources. Throughout the life-cycle of each machine learning model, skilled ML engineers (on both training and inference sides) work closely to prepare it for a robust, scalable, and compute/power efficient inferencing on a resource-constrained hardware accelerator. Such a close working relationship is key to fast and successful deployment of intelligent systems on the car.

Cruise is looking for a Deep Learning Inference Engineer to help us deploy highly efficient machine learning models and build the most intelligent software stack fo r an autonomous car.

In this position, you will work closely with machine learning engineers from different AV Engineering teams (e.g. Computer Vision, Perception), covering different m achine learning algorithms across the AV software stack.

If you're interested in optimizing machine learning inference on different hardware accelerators, and want to test your skills with real-world (and practical) appli cations in the autonomous vehicle domain.

What you will be doing:

• Design and develop scalable and robust software for executing ML inference on the car
• Analyze, optimize and tune performance of ML models on different hardware accelerators
• Provide feedback to ML engineers about choices of operations, model architectures, and parameters
• Collaborate with multi-functional agile teams of AV engineers to guide the direction of inferencing and provide requirements and feature requests for hardware vend ors
• Closely follow industry and academic developments in the inferencing domain and provide performance guidelines and standard methodologies for other ML engineers

What you must have:

• MS, or higher degree, in CS/CE/EE, or equivalent in industry experience
• 2+ years of experience in the field of machine learning deployment
• Extensive experience with ML accelerators and hardware architecture
• Extensive experience with ML deployment software (e.g. TensorRT, TF Lite, etc)
• Extensive experience with standard ML frameworks like Tensorflow, Caffe, Torch
• You should be comfortable writing production-quality code in C++
• You should be familiar with performance analysis, debugging, and optimization

Bonus points!

• GPU programming (e.g. CUDA, OpenCL)
• Experience with ML deployment on edge/mobile devices
• Experience with writing robust, safety-critical code

Apply Online at Cruise