Job Title
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
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
