Posted 11 days ago
Senior Silicon ML Engineer
@ Cognichip
Toronto, Ontario
Overview
Cognichip is hiring a Senior Silicon ML Engineer to fuse chip design and machine learning into end-to-end silicon design flows. The role builds AI-enabled silicon design and verification workflows, curates domain datasets, and turns research prototypes into production systems. The posting states a full-time position with competitive compensation including equity, but gives no location or schedule.
Responsibilities:
- Design AI-enabled silicon design and verification workflows
- Curate and structure silicon design and verification datasets
- Encode domain rules and expert feedback into ML pipelines
- Collaborate with chip design and verification engineers
- Turn research prototypes into production-quality systems
Requirements summary:
- BS plus 4+ years, MS plus 3+ years, or PhD plus 2+ years experience
- Strong Python programming skills, PyTorch preferred
- Experience turning prototypes into production systems
- Experience with messy real-world data and quality metrics
- Exposure to hardware design, verification or EDA workflows
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-11-02
- First seen by our source
- 2026-11-14
- Source record updated
- 2026-11-14
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Experience | 4+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required), Master’s degree (required), Doctorate (required) |
| Fields of study | Computer Science, Electrical Engineering |
| Perks mentioned | Stock or equity |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Cognichip
| Field | Value |
|---|---|
| Open jobs on Jobsy | 4 |
Senior Silicon ML Engineer
Senior Silicon ML Engineer
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
- 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
- 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
- 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.
- 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
Journal
Only you can see this. Kept on this device, and in your account when you sign in.