GPU Compute, MLIR Engineer

Weekday (YC W21)

GPU Compute & MLIR Engineer optimizing AI workloads for a client. Designing, optimizing, and deploying GPU compute kernels while enhancing MLIR compiler backends.

Posted 7/1/2026full-timeRemote • 🇮🇳 IndiaMid-LevelSenior💰 ₹2,000,000 - ₹10,000,000 per yearWebsite

About the role

Key responsibilities & impact

Develop and optimize GPU compute kernels targeting OpenCL and Vulkan compute backends for high-throughput AI/ML workloads.
Design, build, and extend MLIR dialects across multiple abstraction levels—including frontend dialects, graph-level IR, tensor IR (e.g., Linalg, Tensor, TOSA), and runtime/low-level dialects—to enable efficient end-to-end model compilation.
Implement and maintain MLIR-based compiler passes and transformations, including tiling, fusion, bufferization, vectorization, and lowering pipelines targeting OpenCL and Vulkan GPU backends.
Conduct profiling and bottleneck analysis of compiled kernels using GPU counters and vendor-specific profilers, and drive performance improvements through compiler-level optimizations.
Build and maintain GPU runtime infrastructure for both OpenCL and Vulkan, including memory management, pipeline setup, command buffer orchestration, and resource scheduling.
Develop and extend code generation pipelines, enabling automatic lowering from tensor IR through MLIR to efficient OpenCL and Vulkan GPU kernels.
Implement performance-critical schedules—including tiling, loop fusion, parallelism, and caching strategies—within MLIR-based backends targeting OpenCL and Vulkan runtimes.
Collaborate with framework teams to optimize end-to-end model lowering for computer vision and LLM workloads using MLIR compilation stacks.
Design and implement robust compiler and runtime components using modern C/C++, leveraging advanced programming paradigms for high-performance systems.

Requirements

What you’ll need

Strong hands-on experience with the MLIR framework, including authoring and extending custom dialects, writing compiler passes, and building end-to-end lowering pipelines.
Deep expertise across MLIR abstraction levels:
- Frontend dialects – ingestion and representation of ML models (e.g., TOSA, StableHLO, ONNX-MLIR)
- Graph-level IR – high-level operation fusion, shape inference, and graph transformations
- Tensor IR level – structured operation representation using Linalg, Tensor, and Vector dialects; tiling and fusion strategies
- Runtime/low-level dialects – Bufferization, MemRef, SCF, GPU, and LLVM dialects for final code generation
Strong hands-on experience in OpenCL programming, including kernel development, memory model, work-group/work-item optimization, and OpenCL runtime management.
Solid understanding of Vulkan compute programming, including descriptor management, compute pipelines, synchronization primitives, and Vulkan runtime internals.
Strong understanding of GPU architecture, memory hierarchies, and asynchronous compute.
Proficiency in C/C++ for system-level development.
Experience with kernel profiling and bottleneck analysis on GPU platforms.
Strong background in machine learning fundamentals, covering both Computer Vision (CV) and Large Language Model (LLM) workloads.

Benefits

Comp & perks

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Develop and optimize GPU compute kernels targeting OpenCL and Vulkan compute backends for high-throughput AI/ML workloads.
Design, build, and extend MLIR dialects across multiple abstraction levels—including frontend dialects, graph-level IR, tensor IR (e.g., Linalg, Tensor, TOSA), and runtime/low-level dialects—to enable efficient end-to-end model compilation.
Implement and maintain MLIR-based compiler passes and transformations, including tiling, fusion, bufferization, vectorization, and lowering pipelines targeting OpenCL and Vulkan GPU backends.
Conduct profiling and bottleneck analysis of compiled kernels using GPU counters and vendor-specific profilers, and drive performance improvements through compiler-level optimizations.
Build and maintain GPU runtime infrastructure for both OpenCL and Vulkan, including memory management, pipeline setup, command buffer orchestration, and resource scheduling.
Develop and extend code generation pipelines, enabling automatic lowering from tensor IR through MLIR to efficient OpenCL and Vulkan GPU kernels.
Implement performance-critical schedules—including tiling, loop fusion, parallelism, and caching strategies—within MLIR-based backends targeting OpenCL and Vulkan runtimes.
Collaborate with framework teams to optimize end-to-end model lowering for computer vision and LLM workloads using MLIR compilation stacks.
Design and implement robust compiler and runtime components using modern C/C++, leveraging advanced programming paradigms for high-performance systems. 🎯 Requirements
Strong hands-on experience with the MLIR framework, including authoring and extending custom dialects, writing compiler passes, and building end-to-end lowering pipelines.
Deep expertise across MLIR abstraction levels:
- Frontend dialects – ingestion and representation of ML models (e.g., TOSA, StableHLO, ONNX-MLIR)
- Graph-level IR – high-level operation fusion, shape inference, and graph transformations
- Tensor IR level – structured operation representation using Linalg, Tensor, and Vector dialects; tiling and fusion strategies
- Runtime/low-level dialects – Bufferization, MemRef, SCF, GPU, and LLVM dialects for final code generation
Strong hands-on experience in OpenCL programming, including kernel development, memory model, work-group/work-item optimization, and OpenCL runtime management.
Solid understanding of Vulkan compute programming, including descriptor management, compute pipelines, synchronization primitives, and Vulkan runtime internals.
Strong understanding of GPU architecture, memory hierarchies, and asynchronous compute.
Proficiency in C/C++ for system-level development.
Experience with kernel profiling and bottleneck analysis on GPU platforms.
Strong background in machine learning fundamentals, covering both Computer Vision (CV) and Large Language Model (LLM) workloads. Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Reservoir Engineer 🔥 11 hours ago bp 10,000+ employees ⚡ Energy Website LinkedIn All Job Openings Reservoir Engineer advising partners on Production Management for BP's integrated team. Collaborating on resource progression and reservoir management in Gas & Low Carbon Energy. 🇮🇳 India – Remote 💰 Post-IPO Equity on 2024-09 ⏰ Full Time 🟡 Mid-level 🟠 Senior 👷🏻‍♀️ Engineer Forward Deployed Engineer 🕒 Yesterday LiveKit 11 - 50 🔌 API 🤖 Artificial Intelligence 📡 Telecommunications Website LinkedIn All Job Openings Forward Deployed Engineer at LiveKit designing and implementing real-time communication applications. Collaborate with customers on real-time audio, video, and AI application scaling. 🇮🇳 India – Remote 💵 ₹9M - ₹11M / year 💰 Venture Round on 2022-09 ⏰ Full Time 🟡 Mid-level 🟠 Senior 👷🏻‍♀️ Engineer Cloud Distributed Systems Node.js Python Rust Go Next.js Engineer 🕒 Yesterday Shuru 51 - 200 🤖 Artificial Intelligence 🤝 B2B 🏢 Enterprise Website LinkedIn All Job Openings Next.js Engineer developing scalable web applications for Shuru Technologies. Collaborating with teams to deliver reliable user experiences using modern web technologies. 🇮🇳 India – Remote ⏰ Full Time 🟢 Junior 🟡 Mid-level 👷🏻‍♀️ Engineer AWS GraphQL JavaScript Material UI Next.js React Redux TypeScript Polyglot Engineer 🕒 5 days ago PeerIslands 11 - 50 🤖 Artificial Intelligence ☁️ SaaS 🏢 Enterprise Website LinkedIn All Job Openings Polyglot Developer responsible for designing and implementing software architectures remotely. Collaborating with teams and mentoring developers across multiple programming languages. 🇮🇳 India – Remote ⏰ Full Time 🟡 Mid-level 🟠 Senior 👷🏻‍♀️ Engineer AWS Azure Cloud Distributed Systems Docker Google Cloud Platform Java Kubernetes Microservices Node.js NoSQL Python Ruby SQL Go SaaS Engineer – Atlassian 🕒 5 days ago SRM Technologies 501 - 1000 ☁️ SaaS Website LinkedIn All Job Openings Atlassian Platform Engineer supporting and enhancing Dropbox’s Atlassian ecosystem, focusing on administration and operational excellence. Hands-on role improving platform reliability and reducing technical debt. 🇮🇳 India – Remote ⏰ Full Time 🟡 Mid-level 🟠 Senior 👷🏻‍♀️ Engineer Cloud Groovy JavaScript Python View More Engineer Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs

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Hard Skills & Tools

GPU Compute KernelsMLIR DialectsCompiler PassesKernel ProfilingMemory ManagementTiling StrategiesVectorizationBufferizationAsynchronous ComputeGraph Transformations