10 months ago

Libraries Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Design and implement core abstractions for the Mojo Standard Library and kernel libraries, enabling developers to build and integrate with AI systems efficiently. Collaborate with compiler, kernel, and runtime teams to define ergonomic, high-performance APIs, and optimize library functionality for GPU/CPU performance, memory efficiency, and hardware utilization. Contribute to Modular’s open source GitHub project and support high-quality community contributions.

Location: United States, Canada

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Partner with Modular compiler, kernel, and runtime teams to design ergonomic, expressive, performance-conscious APIs.
•Design and implement abstractions that support GPU/CPU kernel and algorithm development and optimization for GenAI inference.
•Optimize library functionality for performance, memory efficiency, and hardware utilization.
•Participate in design discussions and code reviews to maintain high engineering standards.
•Collaborate with other engineering teams to align the standard library with broader platform needs.

Travel: Low travel

Pay and Benefits

Salary: USD 167,000 - 286,000 annually

Perks:Health Insurance401kPaid LeaveEquity

Key Requirements

•Experience with GPU programming languages such as CUDA or OpenCL.
•Deep understanding of GPU architecture (e.g., memory hierarchies, tensor cores) and its impact on algorithms and API design.
•Proficiency in modern systems languages (C++, Rust, or Swift) with strong low-level performance optimization and memory management skills.
•Hands-on open source experience through meaningful contributions or maintaining/reviewing community submissions.
•Collaborative mindset and drive to solve complex technical challenges in a high-performing team.

Experience:Open sourceGPU programmingGenAIAI infrastructure

Skills:CollaborationProblem-solvingIntellectual curiosityPerformance focus

Tech Stack:CUDAOpenCLC++RustSwiftPTXSASSCUTLASSTritonMojoLLVMMLIRPythonGitHub

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Modular

Provides infrastructure and developer tools to build, deploy, and scale large AI models and foundation-model applications, including model hosting, orchestration, and SDKs to accelerate AI product development.

Industry: AI & Machine Learning

Website

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Modular

10 months ago

Libraries Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: United States, Canada

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Partner with Modular compiler, kernel, and runtime teams to design ergonomic, expressive, performance-conscious APIs.
•Design and implement abstractions that support GPU/CPU kernel and algorithm development and optimization for GenAI inference.
•Optimize library functionality for performance, memory efficiency, and hardware utilization.
•Participate in design discussions and code reviews to maintain high engineering standards.
•Collaborate with other engineering teams to align the standard library with broader platform needs.

Travel: Low travel

Pay and Benefits

Salary: USD 167,000 - 286,000 annually

Perks:Health Insurance401kPaid LeaveEquity

Key Requirements

•Experience with GPU programming languages such as CUDA or OpenCL.
•Deep understanding of GPU architecture (e.g., memory hierarchies, tensor cores) and its impact on algorithms and API design.
•Proficiency in modern systems languages (C++, Rust, or Swift) with strong low-level performance optimization and memory management skills.
•Hands-on open source experience through meaningful contributions or maintaining/reviewing community submissions.
•Collaborative mindset and drive to solve complex technical challenges in a high-performing team.

Experience:Open sourceGPU programmingGenAIAI infrastructure

Skills:CollaborationProblem-solvingIntellectual curiosityPerformance focus

Tech Stack:CUDAOpenCLC++RustSwiftPTXSASSCUTLASSTritonMojoLLVMMLIRPythonGitHub

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Modular

Industry: AI & Machine Learning

Website