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Ml compiler & systems engineer

Tivoli
Contratto a tempo indeterminato
TECHBIZ GLOBAL OÜ
System Engineer
Pubblicato il 7 giugno
Descrizione

Social network you want to login/join with: TechBiz Global is a leading recruitment and software development company. Our diverse, globally distributed team provides IT recruitment, outstaffing, outsourcing, software development, and different consulting services with a primary focus on making our partners achieve their business goals successfully. With headquarters in Germany we have successful clients all over the world. We can understand your unique needs. Our team has hands-on experience with the challenges that come with rapid growth and the IT sector. That’s why all of our offerings are built with a tech mindset. We are looking for a ML Compiler & Systems Engineer for our client in a hybrid role, preferably based in Paris. Join us to create cutting-edge solutions that drive significant business impact. What You’ll Do Lead the evolution of our high-performance robotics simulation platform Design and implement the compute infrastructure and data flow mechanisms to optimize performance for physics simulation and foundation model training Lead development of our compiler stack, focusing on JIT compilation, LLVM IR, and GPU codegen to minimize compile time and maximize runtime performance Collaborate with the team to improve the compiler's support for differentiable programming, crucial for training neural networks within simulations Stay current on state-of-the-art ML compilers—such as those in torch, Triton, and JAX—and decide which techniques and approaches are best suited for our application Work closely with simulation and robotics engineers to align compiler enhancements with application needs Contribute to relevant open-source projects and participate actively in the broader compiler and systems community What You’ll Bring Strong background in compiler construction, particularly in JIT compilation and LLVM-based code generation Extensive experience with GPU programming models (e.g., CUDA, Vulkan) and understanding of GPU architecture Track record as a core contributor to GPU programming infrastructure—such as Torch, JAX, Mojo, Taichi, or Warp Proven ability to profile and optimize complex systems for performance and scalability Understanding of automatic differentiation and its application in simulation and machine learning contexts Excellent communication skills and a collaborative approach to problem-solving Enthusiasm for contributing to and engaging with open-source communities J-18808-Ljbffr

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