Job Description:
Altera is one of the world's leading providers of programmable solutions. With a renewed focus on agility and software-first useability, Altera is shaping the future of computing by providing flexible technology, empowering innovators with scalable products, from high-performance to power- and cost-optimized devices for cloud, network, and edge applications. Join Altera’s FPGA AI Suite team to create, build, and deliver our future FPGA technology.
As a Senior Hardware Engineer, you will be responsible for integrating the AI Suite machine learning inference IP into example FPGA designs, including both SoC and PCIe-attach designs. Your work will include optimizing these designs to improve performance and usability. You are a strong RTL engineer and will contribute to improving the machine learning IP and its supporting modules. You enjoy working in a mostly onsite team environment, with close collaboration and physical access to hardware when needed.
Qualifications
- Bachelor’s Degree or above in electrical engineering or a related field
- 10+ years industry experience writing RTL and developing FPGA system
- The ideal candidate will be familiar with Verilog
- The ideal candidate will be familiar with SoC development and debug tools such as Signal Tap
- Familiarity with Altera FPGAs is a plus
- Familiarity with UVM is a plus
-
Familiarity with C/C++ is a plus
Regular
Shift
Shift 1 (Canada)
Primary Location:
Toronto, Ontario, Canada
Additional Locations:
Posting Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Senior Embedded Software Engineer
@ Embedd 
What we're looking for
At embedd.it, we power hardware-software integration in embedded devices. We turn fragmented semiconductor chip data into configurable digital twins, then deterministically generate code, tests, and documentation – making integration faster, cheaper, and resilient to supply chain shocks.
We’re looking for a true legend – someone with abstract thinking and deep expertise in low-level software development. You’ll build vendor-agnostic tooling for MCU and peripheral integration to solve hardware-software integration once and for all. We work at the intersection of embedded systems, code generation, compilers, and machine learning. It’s your chance to help redefine how low-level development is done.
Responsibilities
- Drive the architecture of the driver structures and system layout
- Define scalable patterns for cross-architectural integration across bare-metal, Zephyr, Linux, and other environments
- Deconstruct complex SoC device trees and translate hardware descriptions into structured internal models for automated reasoning
- Partner with the ML team to shape data and annotation models for AI-driven data-extraction tooling
Qualifications
- 5+ years of experience in embedded systems development, including bare-metal and RTOS-based systems
- Proficiency in C/C++
- Familiarity with firmware configuration, SoC bring-up, and system-level debugging
- Hands-on experience with code generation tools, or low-level compiler/decompiler/emulator technologies
- Strong background in embedded toolchains: compilers, linkers, debuggers, and build systems
- Python or scripting for automation and tooling is a plus
- Experience with functional-safety standards is a plus
Why embedd.it?
- Dynamic, venture-backed team of engineers challenging the status quo 🚀
- Work at the intersection of embedded systems, code generators, compilers, and ML 🤖
- Unusual challenges requiring out-of-the-box abstract thinking 🧠
- Competitive compensation: cash + equity 💰
- Remote work possible 🌍
About Us
embedd.it is a UK-based startup reinventing embedded development. Our platform transforms unstructured semiconductor data into structured digital twins, enabling automatic generation of drivers, tests, and documentation. We're building a single, traceable source of truth to make integration fast, vendor-agnostic, and future-proof.
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