Software Engineers, Programmers at Tesla Incorporated – 8 Openings

Tesla Incorporated – We’re building a world powered by solar energy, running on batteries and transported by electric vehicles. Explore the most recent impact of our products, people and supply chain.

1). Tesla Bot

Location: Worldwide

Summary:

• Create a general purpose, bi-pedal, autonomous humanoid robot capable of performing unsafe, repetitive or boring tasks.
• Achieving that end goal requires building the software stacks that enable balance, navigation, perception and interaction with the physical world.
• We’re hiring deep learning, computer vision, motion planning, controls, mechanical and general software engineers to solve some of our hardest engineering challenges.

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2). FSD Chip

Location: Worldwide

Summary:

• Build AI inference chips to run our Full Self-Driving software, considering every small architectural and micro-architectural improvement while squeezing maximum silicon performance-per-watt.
• Perform floor-planning, timing and power analyses on the design.
• Write robust tests and scoreboards to verify functionality and performance.
• Implement drivers to program and communicate with the chip, focusing on performance optimization and redundancy.
• Finally, validate the silicon chip and bring it to mass production in our vehicles.

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3). Dojo Chip

Location: Worldwide

Summary:

• Build AI training chips to power our Dojo system.
• Implement bleeding-edge technology from the smallest training nodes to the multi-die training tiles.
• Design and architect for maximum performance, throughput and bandwidth at every granularity.
• Dictate physical methodology, floor-planning and other physical aspects of the chip.
• Develop pre-silicon verification and post-silicon validation methods to ensure functional correctness.
• Write compilers and drivers to optimize power and performance for our neural networks throughout the entire Dojo system.
• For more information about Dojo’s arithmetic formats and methods, download our latest whitepaper.

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4). Dojo System

Location: Worldwide

Summary:

• Design and build the Dojo system, from the silicon firmware interfaces to the high-level software APIs meant to control it.
• Solve hard problems with state-of-the-art technology for high-power delivery and cooling, and write control loops and monitoring software that scales.
• Work with every aspect of system design where the limit is only your imagination, employing the full prowess of our mechanical, thermal and electrical engineering teams to create the next-generation of machine learning compute for use in Tesla datacenters.
• Collaborate with Tesla fleet learning to deploy training workloads using our massive datasets, and design a public facing API that will bring Dojo to the masses.

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5). Neural Networks

Location: Worldwide

Summary:

• Apply cutting-edge research to train deep neural networks on problems ranging from perception to control.
• Our per-camera networks analyze raw images to perform semantic segmentation, object detection and monocular depth estimation.
• Our birds-eye-view networks take video from all cameras to output the road layout, static infrastructure and 3D objects directly in the top-down view.
• Our networks learn from the most complicated and diverse scenarios in the world, iteratively sourced from our fleet of millions of vehicles in real time.
• A full build of Autopilot neural networks involves 48 networks that take 70,000 GPU hours to train 🔥.
• Together, they output 1,000 distinct tensors (predictions) at each timestep.

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6). Autonomy Algorithms

Location: Worldwide

Summary:

• Develop the core algorithms that drive the car by creating a high-fidelity representation of the world and planning trajectories in that space.
• In order to train the neural networks to predict such representations, algorithmically create accurate and large-scale ground truth data by combining information from the car’s sensors across space and time.
• Use state-of-the-art techniques to build a robust planning and decision-making system that operates in complicated real-world situations under uncertainty. Evaluate your algorithms at the scale of the entire Tesla fleet.

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7). Code Foundations

Location: Worldwide

Summary:

• Throughput, latency, correctness and determinism are the main metrics we optimize our code for.
• Build the Autopilot software foundations up from the lowest levels of the stack, tightly integrating with our custom hardware.
• Implement super-reliable bootloaders with support for over-the-air updates and bring up customized Linux kernels.
• Write fast, memory-efficient low-level code to capture high-frequency, high-volume data from our sensors, and to share it with multiple consumer processes— without impacting central memory access latency or starving critical functional code from CPU cycles.
• Squeeze and pipeline compute across a variety of hardware processing units, distributed across multiple system-on-chips.

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8). Code Foundations

Location: Worldwide

Summary:

• Build open- and closed-loop, hardware-in-the-loop evaluation tools and infrastructure at scale, to accelerate the pace of innovation, track performance improvements and prevent regressions.
• Leverage anonymized characteristic clips from our fleet and integrate them into large suites of test cases.
• Write code simulating our real-world environment, producing highly realistic graphics and other sensor data that feed our Autopilot software for live debugging or automated testing.

Deadline: Not Stated

How to Apply: Interested candidates should Click Here to apply.