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Autonomous vehicle engineer – sensor fusion/path planning

Source Group International Autonomous Driving & Electric Transportation

This is a Full-time position in San Francisco, CA posted December 21, 2019.

My clients are perceived to be one of the most exciting autonomous vehicle start-up’s in stealth mode.

Currently they are a team of quantitative scientists and engineers who are building the next generation of AI algorithms for self-driving cars, drones and consumer robots.

In particular focus is on building the core AI perception software for L4-L5 autonomy whilst utilizing sensors such as vision and radar as well as sensor fusion with Lidar.

By heavily utilizing mathematical modelling and deep learning, without human annotation they are tackling the bottleneck of getting to L4.

The current team consists of researchers from top schools like Harvard, MIT, Stanford, and Caltech and engineers from companies like Google, Stripe, Quora, and more.

The software is already available as an SDK, which has been purchased or deployed by 6 of the top 10 car manufacturers in the world.

While their technology is being scaled to solve all of the subtasks and corner cases needed for L4 deployment, currently this is being marketed for partial autonomy in consumer vehicles.

The goal is to integrate the software you help build into millions of consumer vehicles in the coming years.

My clients are already demonstrating capabilities in 3D Perception/Depth Estimation that exceeds what is widely viewed as the market standard (this has been verified by their clients’ due diligence).

Not only are they are able to build full dense 3D reconstructed images of the world in real-time on a single GPU, but they have also made advancements that allow them to use stereo images something we are yet to see in other companies.

Their deep learning approach to self-driving is uniquely data and capital-efficient, allowing them to get to market quickly.

Responsibilities: Develop sensor fusion, path planning, and control algorithms across the spectrum of L2+, L3, and L4 products and software demonstrations.

Develop new sensor fusion algorithms to integrate perception functionality into the driving system, focused on automotive-grade radar and lidar, including next-generation sensors.

Use cloud computing abstractions to design and implement algorithm validation software at scale, for testing new functionalities.

Provide design guidance for effective simulation testing of algorithms.

Design software integration plans for OEM vehicles.

Identify algorithmic changes needed for adapting to various sensor sets and middlewares.

Work with systems engineers to make the integrations a reality.

What We’re Looking For Master’s degree with at least three years of industry experience, or PhD with at least one year of industry experience.

Fields of study: EE, MechE, CS, Physics.

Fluency in Python, familiarity with C++.

Experience with numerical algorithms in Matlab, Python, or Julia.

Preferred: Familiarity with real time / embedded operating systems.

Preferred: Prior experience with sensor fusion and path planning or related mathematical problems.

Preferred: Experience designing mathematical models for integrating noisy measurements to produce useful control signals.

Preferred: Engineering experience integrating numerical algorithms into embedded platforms as well as simulation test harnesses.