Develop platform driver code, perform diagnostics testing, collaborate with hardware engineers, and support system deployment in AI datacenters.
Job Description: Platform/Diagnostics Engineer
Company Description: As an AI infrastructure startup, we are developing innovative
systems to enable large-scale AI deployments. Our team comprises industry veterans who are passionate about building the sophisticated systems that support the next generation of computing in a fast-paced startup environment.
Job Responsibilities:
- Write platform driver code both in kernel and user space. Write diagnostics code to test and verify hardware is working as designed.
- Participate in and lead design reviews with peers to decide on the best solutions for platform/diagnostic architecture.
- Collaborate with hardware engineers to come up with custom tests to stress hardware design.
- Participate in all parts of system enablement ranging from system bring up to be ready to be deployed in AI datacenters.
- Support diagnostic tests for the systems in Manufacturing/EMI/Safety/MDVT/Packaging.
- Be a part of shaping a startup - define company culture, challenge and change the ways things are done, and contribute to determining the future of the company
Qualifications: Strong problem-solving skills, quick learning and excitement for a collaborative startup environment are the most important things we're looking for. When you arrive, we make sure to give you projects that you are both excited for and that align with your experience and expertise. The list below are some of the qualifications that will help but aren’t essential to thriving here.
- Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering or a related field
- Proficiency in the following languages: Python, C
- Solid understanding of systems software, including embedded systems and distributed systems
- Ability to read schematics/component datasheets
- Familiarity with container technologies (e.g., Docker) and L2 networking protocols is a plus.
- Good communication skills and ability to work collaboratively in a team
- Confidence to both ask questions and take ownership of your project(s)
Top Skills
C
Docker
Python
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What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
