Is the Inference Intern role remote?

No — this is an on-site role in San Jose.

Where is the role based?

Etched is hiring for this position in San Jose.

What's the tech stack?

Joblaze extracted these technologies from the posting: C++, GPUs, Infiniband, JAX, Linux, NVLink.

What seniority level is this role?

Etched targets intern candidates for this position.

Is this full-time or contract?

Internship for this Inference Intern role at Etched.

Inference Intern at Etched

Joblaze summary

The Inference Intern at Etched will engage in the design and optimization of compute architectures specifically for AI inference workloads, tackling complex architectural challenges. Key skills include proficiency in Python and C++, along with a solid understanding of distributed systems and performance-sensitive software. This role is ideal for candidates pursuing advanced degrees in computer science or related fields, particularly those with experience in accelerator architectures and transformer models. Etched fosters a collaborative environment where engineering and research intersect, emphasizing hands-on mentorship from experienced professionals.

Joblaze insights

Listed 3 days ago — first seen on Joblaze September 21, 2026. Last confirmed on Etched's careers page September 23, 2026.
Python appears in 33.3% of 60 comparable intern ai/ml roles in United States; Linux appears in 3.3% of 60 comparable intern ai/ml roles in United States.

Quick facts

Is the Inference Intern role remote?: No — this is an on-site role in San Jose.
Where is the role based?: Etched is hiring for this position in San Jose.
What's the tech stack?: Joblaze extracted these technologies from the posting: C++, GPUs, Infiniband, JAX, Linux, NVLink.
What seniority level is this role?: Etched targets intern candidates for this position.
Is this full-time or contract?: Internship for this Inference Intern role at Etched.

From the original posting

Job Summary

We are seeking talented Fall '26, Spring '27, and Summer '27 Inference Architecture interns to join our team and contribute to the design of next-generation AI accelerators. This role focuses on developing and optimizing compute architectures that deliver exceptional performance and efficiency for inference workloads. You will work on cutting-edge architectural problems and performance modeling over the course of your internship.

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.
Assist in building, enhancing, and scaling our runtime, including multi-node inference, intra-node execution, state management, and robust error handling.
Contribute to optimizing routing and communication layers using our collectives.
Utilize performance profiling and debugging tools to identify bottlenecks and correctness issues.
Develop and leverage a deep understanding of our architecture to co-design both HW instructions and model architecture operations to maximize model performance
Implement high-performance software components for the Model Toolkit

Progress towards a Bachelor’s, Master’s, or PhD degree in computer science, computer engineering, applied mathematics, or a related field
Proficiency in Python, C++
Understanding of performance-sensitive or complex distributed software systems, e.g. Linux internals, accelerator architectures (e.g. GPUs, TPUs), Compilers, or high-speed interconnects (e.g. NVLink, InfiniBand).
Ported applications to non-standard accelerator hardware or hardware platforms.
Deep knowledge of transformer model architectures and/or inference serving stacks (vLLM, SGLang, etc.)

Strong candidates may have some experience with

Proficiency in Rust
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.
Familiarity with PyTorch or JAX.
Math competitions (AIME, AMC, etc)

We encourage you to apply even if you do not believe you meet every qualification.

Program details

12-week paid internship
Generous housing support for those relocating
Daily lunch and dinner in our office
Based at our office in San Jose, CA
Direct mentorship from industry leaders and world-class engineers
Opportunity to work on one of the most important problems of our time

For any questions, contact internships@etched.com.

Standard company text repeated across Etched's postings is omitted here.

Inference Intern

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