AI Engineer

This role is part of the Jobright TNT - the private hiring network connecting top talent with top AI startups like Perplexity, Mercor, Cresta, Suno and 150 more.

This is not a mass job posting. Only select, high-signal candidates are invited to Jobright TNT and recommended directly to hiring teams

Hiring Company: TenX Semi

One-liner: TenX Semi is reinventing how chips are designed to provide a seismic shift in the industry. The AI Engineer will build core AI systems for generating and optimizing chip designs, developing models that write RTL and improve through verification feedback.

Why Join Us:

• Build and improve AI that is redefining how next-generation chips are designed and verified while leveraging self-verifying-and-fixing loop using AI and formal methods.

• Founded by a Stanford University professor (Prof. Subhasish Mitra) and former Samsung EVP Suk Hwan Lim and a world-class team from Google, Meta, Apple, Broadcom, Stanford, Synopsys, well-funded with eight-figure backing raised from top-tier VCs.

• Work at the intersection of AI, formal verification, and chip design, one of the most technically challenging but rewarding problems in engineering.

• Join an early team with the opportunity to shape both the product and the future of AI-native chip design.

Role Responsibilities

• Build Code Generation Models: Develop and fine-tune LLMs that generate syntactically and functionally correct Verilog/SystemVerilog with the best power-performance-area

• Develop Derivative Design Generation: Build systems that take existing RTL and a delta specification, and produce modified RTL that implements the requested changes while preserving correctness

• Design Space Exploration: Build algorithms that automatically explore the design space, proposing delta specs that improve PPA (power, performance, area) while maintaining functionality

• Optimize Inference: Ensure our models run fast enough for interactive use. You will optimize inference latency and throughput for production deployment

• Curate Training Data: Develop pipelines to collect, clean, and curate training data from verified designs. Data quality is model quality

Qualifications

Required

• LLM/Transformer Expertise: Deep experience with dataset preparation and creation, large language models, transformer architectures, and their training. You understand attention mechanisms, tokenization strategies, and scaling laws

• Code Generation Experience: Worked on code generation systems. You understand the unique challenges of generating executable code versus natural language

• PyTorch/JAX Proficiency: Expert-level skills in PyTorch or JAX. You can implement custom model architectures and training loops

• Distributed Training: Experience training large models across multiple GPUs/TPUs

• Reinforcement Learning: Familiarity with RL concepts

Preferred

• Experience at AI labs and/or AI startups

• Background in compilers, program synthesis, or formal methods

• Understanding of hardware design concepts (RTL, synthesis, timing, PPA)

• Experience with code LLMs

• MS or PhD in Computer Science with ML focus

How can I join Jobright TNT:

If this is your first time applying to a Jobright TNT role, the process works as follows:

1. Apply to your first Jobright TNT role

2. We review your background to determine if you meet the TNT quality bar

3. If qualified, your application is directly recommended to the employer

4. Once accepted into TNT, you may be:

- Invited to apply for other exclusive TNT-only roles

- Invited to private, invite-only hiring events with top startups

You will be notified of your TNT selection result.

PS: All Jobright TNT roles are 100% real, directly hired by top AI startups we partner with, and come with priority review and higher response rates than the normal application queue.