Senior Silicon Ml Engineer

Senior Silicon ML EngineerCognichip
Location: Toronto, ON, CA FULL_TIME
Salary: 150,000–180,000 CAD / year
At Cognichip, we’re not just building AI—we’re redefining what’s possible at the nexus of silicon design and machine learning. As a Silicon ML Engineer on our team, you’ll fuse knowledge of chip design and ML into end-to-end silicon design flows. If you thrive on pushing the envelope of domain‑specific research and translating cutting‑edge ideas into production‑grade systems, this is your stage.
Core Responsibilities
Design and implement AI-enabled silicon design and verification workflows with explicit incorporation of hardware domain knowledge and constraints
Lead system architecture and integration with internal silicon design tools and workflows in LLM‑based agentic systems
Own end‑to‑end the curation, cleaning, and structuring of silicon design and verification datasets or ML/LLM/agentic system with domain‑aware labeling and quality controls
Encode domain structure, rules, and expert feedback into ML/DL model pipelines, prompts, evaluation, and system logic
Collaborate directly with other chip design and verification engineers to ensure domain correctness and practical usability
Build AI for hardware research prototypes and convert them into scalable, production‑quality systems integrated with design flows
Produce technical documentation and communicate design decisions and tradeoffs to cross‑functional stakeholders
Required Qualifications
BS in Computer Science, Electrical Engineering, or a related field plus 4+ year of full- time industry experience OR MS in Computer Science, Electrical Engineering, or a related field plus 3+ year of full-time industry experience OR PhD in a relevant field with 2+ year of applied research or industry experience
Strong programming skills in Python (PyTorch or similar ML frameworks preferred)
Demonstrated ability to turn research prototypes to production systems
Experience working with messy, real-world data and defining quality metrics
Demonstrated exposure to hardware design, verification, or EDA workflows through coursework, research, or industry work
Proven track record of collaboration with with other deeply technical teams
Preferred Qualifications
Background or exposure to silicon design / EDA workflows (e.G., RTL, verification, specs, UVM, synthesis) and hardware description language, e.G., verilog or systemverilog
Industry experience with LLMs, agentic systems, or domain‑adapted AI systems
Experience with synthetic or programmatic data generation, simulation‑driven data, or otherwise automated dataset construction
Experience using Databricks or similar large‑scale data processing platforms
Experience collaborating in fast‑moving, cross‑functional teams
What We Offer
Work on foundational and unsolved problems at the frontier of AI and hardware
Real ownership in your work that directly shapes core product capabilities.
Work with a team of high‑caliber collaborators at the intersection of AI, cloud, and semiconductor design.
A culture of innovation, precision, and impact, where your work directly shapes the future of engineering.
Competitive compensation package, including equity participation.
Who This Role Is Great For
Engineers excited to work across ML, systems, and silicon
Mid‑career ML engineers with strong fundamentals and real‑world experience
Early‑career PhD graduates who want to see research ideas actually ship
People who like ambiguity and turning vague problems into concrete systems
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