Full-Time

Embedded Software Engineer

Extropic

Extropic

11-50 employees

Energy-efficient probabilistic silicon AI accelerator

Compensation Overview

$150k - $250k/yr

Boston, MA, USA

In Person

Category
Software Engineering (1)
Required Skills
Python
C/C++
Linux/Unix
Requirements
  • Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Computer Science, or related field.
  • 5+ years of hands-on experience in embedded firmware and Linux software development.
  • Strong proficiency in C, C++, and Python, with emphasis on embedded and deeply embedded programming.
  • Deep experience with bare-metal firmware development, interrupt-driven systems, and hardware bring-up.
  • Proven experience with embedded Linux (build systems, user-space applications, drivers, device trees).
  • Hands-on experience with heterogeneous multi-core RISC-V and ARM processors, such as Cortex-R5 and Cortex-A53
  • Strong understanding of multi-threaded and multi-core software design principles.
  • Experience developing and debugging drivers and applications using I2C, SPI, UART, DMA, and other common peripherals.
  • Strong lab skills: oscilloscopes, logic analyzers, protocol analyzers, power measurement, and signal debugging.
  • Proficiency with software debuggers (GDB, OpenOCD, Lauterbach, etc.).
  • Ability to analyze, troubleshoot, and optimize system performance across the entire hardware/software boundary.
Responsibilities
  • Architect, design, and implement embedded software across bare-metal, RTOS, and embedded Linux environments.
  • Develop firmware, Linux drivers, user-space applications, and host-PC tools supporting the full embedded software stack.
  • Work with heterogeneous multi-core SoCs (e.g., Cortex-R5 real-time cores and Cortex-A53 application cores), enabling inter-processor communication, synchronization, and resource sharing.
  • Implement multi-threaded, multi-core software architectures with attention to power, performance, determinism, and reliability.
  • Develop and maintain low-level drivers for peripherals including SPI, I2C, UART, GPIO, timers, and DMA engines.
  • Debug real-time embedded systems using JTAG/SWD debuggers, in-circuit emulators, and software diagnostic tools.
  • Perform hands-on system characterization using oscilloscopes, logic analyzers, and protocol analyzers (SPI/I2C/UART, LVDS, Ethernet, USB, etc.).
  • Write clean, robust, well-tested C/C++ code for bare-metal and Linux environments.
  • Develop Python tools for automation, test, and host-side applications.
  • Collaborate closely with hardware, FPGA, and systems engineers to bring up new boards, validate interfaces, and resolve integration issues.
  • Contribute to system architecture decisions, design reviews, and technical documentation.
Desired Qualifications
  • Experience with Yocto/PetaLinux, Buildroot, or similar embedded Linux build systems.
  • Familiarity with IPC mechanisms (RPMsg, shared memory, message queues) in heterogeneous SoC environments.
  • Experience integrating firmware with FPGA-based systems or custom ASIC’s.
  • Familiarity with FPGA embedded software environments such as AMD/Xilinx Vitis
  • Knowledge of network protocols and experience building socket-based host-PC applications.
  • Experience with continuous integration, test automation, and version control (Git).
  • Strong analytical and problem-solving ability.
  • Excellent communication skills for cross-team collaboration.
  • Self-starter attitude and ability to take ownership of complex features from architecture to deployment.
  • Comfortable working in a fast-paced, hands-on engineering environment.

Extropic develops a silicon-based probabilistic chip and a full-stack hardware platform to accelerate generative AI. Its approach, thermodynamic accelerated computing, uses natural matter fluctuations as a computational resource to run probabilistic and physics-informed operations, notably Monte Carlo simulations, with lower energy use. This differentiates Extropic from conventional AI chips by focusing on probabilistic computation and energy efficiency as core design pillars, and it provides an end-to-end hardware solution rather than a single accelerator. The goal is to scale large AI models more efficiently by reducing power consumption and bypassing bottlenecks in traditional hardware.

Company Size

11-50

Company Stage

Seed

Total Funding

$14.1M

Headquarters

Austin, Texas

Founded

2022

Simplify Jobs

Simplify's Take

What believers are saying

  • XTR-0 devkit runs small ML workloads with superior efficiency since 2025.
  • THRML library accelerates thermodynamic algorithm development on GitHub.
  • TSUs address AI energy bottlenecks, enabling scalable generative models.

What critics are saying

  • Nvidia locks customers with CUDA, crushing Extropic in 6-12 months.
  • Rain AI and Normal Computing capture contracts with faster tape-outs.
  • Thermal flaws prevent TSU scaling beyond prototypes in 18-24 months.

What makes Extropic unique

  • Extropic develops TSUs harnessing thermal noise for probabilistic AI sampling.
  • Thermodynamic chips enable 100-10,000x energy efficiency over GPUs for generative AI.
  • DTM model outperforms MEBMs in multimodal data sampling efficiency.

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Your Connections

People at Extropic who can refer or advise you

Benefits

Health Insurance

401(k) Retirement Plan

Remote Work Options

Paid Vacation

Flexible Work Hours

Conference Attendance Budget

Professional Development Budget

Wellness Program

Mental Health Support

Stock Options

Company Equity

Phone/Internet Stipend

Home Office Stipend

Hybrid Work Options

Family Planning Benefits

Fertility Treatment Support

Growth & Insights and Company News

Headcount

6 month growth

-9%

1 year growth

-9%

2 year growth

7%
ArcTern Ventures
Mar 26th, 2026
Normal Computing raises $50M from Samsung Catalyst to tackle soaring AI chip costs and power demands.

Normal Computing raises $50M from Samsung Catalyst to tackle soaring AI chip costs and power demands. Normal Computing has raised $50 million in a round led by Samsung Catalyst as the startup pursues a two-pronged bet on the future of AI hardware: using AI to help semiconductor companies design chips more efficiently, while also developing a new kind of processor aimed at reducing energy use. New investors include Galvanize, Brevan Howard Macro Venture Fund, and ArcTern Ventures, alongside existing backers Celesta Capital, Drive Capital, Eric Schmidt's First Spark Ventures, and Micron Ventures. CEO Faris Sbahi told Fortune the company's software platform is already being used by more than half of the top 10 semiconductor companies by revenue, as it targets one of the industry's biggest challenges: the rising cost and complexity of designing advanced AI chips, where even small errors can lead to expensive delays and rework. Designing advanced AI chips has become so complex that even getting a design to "tape-out" - the point where it's finalized for manufacturing - is increasingly prone to costly failure. Modern AI chips, which pack in tens of billions of transistors to support today's frontier models, can cost more than $500 million to develop before a single unit ships. Normal, founded in 2022 by former engineers and scientists from Google Brain, Google X, and Palantir, is also using its chip design software internally to build its own experimental AI hardware. It has already taped out a prototype chip using the company's "thermodynamic" approach, which uses the inherent randomness of physical systems to compute more efficiently than traditional GPUs. It's an early step in a longer-term effort to significantly reduce the energy demands of AI. "The mission of the company is to go after this so-called AI energy crisis," said Sbahi. "Data centers are expected to hit an energy wall around 2030, and most of the strategy now is to find new ways to acquire more energy - but our position is to solve the problem in terms of the hardware that we're using." Seeking alternatives to existing AI hardware. Normal Computing is part of a growing group of startups exploring alternatives to conventional AI hardware, including Unconventional AI, led by former Intel AI chief Naveen Rao, which raised a $475 million seed round in January led by Andreessen Horowitz and Lightspeed Ventures. Another is Extropic, which is developing probabilistic AI chips based on a different technical approach. Sbahi said the company chose the name "Normal Computing" to reflect its view that its approach is closer to how computation should naturally work. "We think this is the more normal way of computing," he said, pointing to how the company's software and hardware are designed to align with the underlying physics. "The software really matches the hardware." While building energy-efficient AI chips is the company's long-term goal - initially focused on inference workloads for generative AI - the current fundraise will focus on scaling Normal's commercial software business. "Hopefully someday we'll be integrated into mainstream semiconductor design manufacturing," said Sbahi. He added that the semiconductor industry's high costs and complexity make it difficult for new approaches to break in, which is why Normal has focused on working with existing chipmakers rather than trying to disrupt the system from the outside. "It's very expensive to make mistakes," he said.

MADSHRIMPS
Mar 18th, 2024
Extropic Intends to Accelerate AI through Thermodynamic Computing

Extropic, a pioneer in physics-based computing, this week emerged from stealth mode and announced the release of its Litepaper, which outlines the company's revolutionary approach to AI acceleration through thermodynamic computing.

PR Newswire
Mar 15th, 2024
Extropic Emerges From Stealth, Aiming To Revolutionize Generative Ai With Physics-Based Ai Processors

The innovative computing paradigm harnesses the power of out-of-equilibrium thermodynamics to merge generative AI with the physics of the worldSAN FRANCISCO, March 15, 2024 /PRNewswire/ -- Extropic, a pioneer in physics-based computing, this week emerged from stealth mode and announced the release of its Litepaper, which outlines the company's revolutionary approach to AI acceleration through thermodynamic computing. Founded in 2022 by Guillaume Verdon, Extropic has been developing novel chips and algorithms that leverage the natural properties of out-of-equilibrium thermodynamic systems to perform probabilistic computations for generative AI applications in a highly efficient manner. Microscope image of an Extropic chip. The Litepaper delves into Extropic's groundbreaking computational paradigm, which aims to address the limitations of current digital hardware in handling the complex probability distributions required for generative AI. Today's algorithms spend around 25% of their time moving numbers around in memory, limiting the speedup achievable by accelerating specific operations. In contrast, Extropic's chips natively accelerate a broad class of probabilistic algorithms by running them physically as a rapid and energy-efficient, physics-based process in their entirety, unlocking a new regime of AI acceleration well beyond what was previously thought achievable

VC News Daily
Mar 15th, 2024
Extropic Emerges From Stealth With $14.1M Seed Funding

Extropic Emerges from Stealth with $14.1M Seed Funding. 2024-03-15

PitchBook
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