Inference Software Engineer

Etched; San Jose (CA); On-site; Full time

Benefits offered by this job

Medical, dental, and vision packages

Housing subsidy of $2k per month

Relocation support for those moving to San Jose

Daily lunch + dinner in the office

Job summary

An innovative AI hardware company in San Jose is looking for talented engineers to support the porting of state-of-the-art AI models to their architecture. Candidates should be proficient in C++ or Rust and have a strong understanding of performance-sensitive distributed software systems. This full-time position offers competitive benefits including a housing subsidy and wellness programs designed to support team members both professionally and personally. Join the team committed to redefining AI infrastructure.

Qualifications

• Proficiency in C++ or Rust.
• Understanding of complex distributed software systems like Linux internals and accelerator architectures.
• Familiarity with deep learning frameworks such as PyTorch or JAX.

Responsibilities

• Support porting state‑of‑the‑art models to our architecture.
• Build, enhance, and scale Sohu’s runtime for multi‑node inference.
• Utilize performance profiling tools to identify bottlenecks.

Skills

Proficiency in C++ or Rust

Understanding of performance-sensitive distributed software systems

Familiarity with PyTorch or JAX

Job description

About Etched

Etched is building the world’s first AI inference system purpose-built for transformers - delivering over 10x higher performance and dramatically lower cost and latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real‑time video generation models and extremely deep & parallel chain‑of‑thought reasoning agents. Backed by hundreds of millions from top‑tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

Key responsibilities

• Support porting state‑of‑the‑art models to our architecture. Help build programming abstractions and testing capabilities to rapidly iterate on model porting.
• Build, enhance, and scale Sohu’s runtime, including multi‑node inference, intra‑node execution, state management, and robust error handling.
• Optimize routing and communication layers using Sohu’s collectives.
• Utilize performance profiling and debugging tools to identify bottlenecks and correctness issues.

You may be a good fit if you have

• Proficiency in C++ or Rust.
• Understanding of performance‑sensitive or complex distributed software systems like Linux internals, accelerator architectures (e.g. GPUs, TPUs), Compilers, or high‑speed interconnects (e.g. NVLink, InfiniBand).
• Familiarity with PyTorch or JAX.
• Ported applications to non‑standard accelerator hardware or hardware platforms.

Strong candidates may also have experience with (Nice‑to‑have qualifications)

• Developed low‑latency, high‑performance applications using both kernel‑level and user‑space networking stacks.
• Deep understanding of distributed systems concepts, algorithms, and challenges, including consensus protocols, consistency models, and communication patterns.
• Solid grasp of Transformer architectures, particularly Mixture‑of‑Experts (MoE).
• Built applications with extensive SIMD (Single Instruction, Multiple Data) optimizations for performance‑critical paths.

Benefits

• Medical, dental, and vision packages with generous premium coverage
  • $500 per month credit for waiving medical benefits
• Housing subsidy of $2k per month for those living within walking distance of the office
• Relocation support for those moving to San Jose (Santana Row)
• Various wellness benefits covering fitness, mental health, and more
• Daily lunch + dinner in our office

How we’re different

Etched believes in the Bitter Lesson. We think most of the progress in the AI field has come from using more FLOPs to train and run models, and the best way to get more FLOPs is to build model‑specific hardware. Larger and larger training runs encourage companies to consolidate around fewer model architectures, which creates a market for single‑model ASICs.

We are a fully in‑person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.