ML Infrastructure Engineer

Are you fascinated by the sheer power of GPUs and their pivotal role in the world of artificial intelligence? Do you thrive on dissecting performance bottlenecks, building robust testing frameworks, and truly pushing the limits of machine learning hardware? Nebius invites a passionate and highly skilled ML infrastructure engineer to join our innovative, globally distributed team. This is your chance to directly influence the development of next generation AI cloud platforms, working alongside some of the brightest minds in the industry, all from the comfort of your home, anywhere in the world.

About Nebius

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full stack AI cloud platform that seamlessly supports developers and enterprises. Our platform covers everything from data and model training through to production deployment, all without the usual cost and complexity of building massive in house AI/ML infrastructure. Nebius is truly built by engineers, for engineers. We embrace and solve the hard problems across compute, storage, networking, and applied AI, from large scale GPU orchestration to inference optimization. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we boast a global footprint with vibrant R&D hubs spread across Europe, the UK, North America, and Israel. Our team of over 1,500 includes hundreds of engineers with deep, specialized expertise spanning hardware, software, and AI R&D.

Overview of the Role

We are searching for an ML Infrastructure Engineer to lead and actively support the comprehensive benchmarking of GPU platforms for machine learning and AI workloads. In this critical position, you will play a vital role in evaluating the performance of GPU based hardware. This involves various deep learning and AI frameworks. Your insights will enable crucial, data driven decisions that directly impact our platform optimization strategies and the development of cutting edge, next generation hardware.

Key Responsibilities

Lead and support comprehensive benchmarking of GPU platforms for various machine learning and AI workloads.
Develop and implement robust testing methodologies and tools to accurately measure GPU performance.
Design and execute experiments to evaluate GPU performance across different deep learning and AI frameworks, including TensorFlow, PyTorch, and others.
Analyze performance data, identify bottlenecks, and provide actionable recommendations for hardware and software optimization.
Collaborate closely with hardware engineers, software developers, and AI researchers to define benchmarking requirements and interpret results.
Stay abreast of the latest advancements in GPU hardware, AI accelerators, and machine learning frameworks.
Contribute to the continuous improvement of our benchmarking infrastructure and processes.

Requirements

Proven experience as an ML/AI Engineer with a strong focus on infrastructure and performance.
Deep understanding of GPU architectures and their optimization for machine learning workloads.
Proficiency in benchmarking tools and methodologies relevant to GPU computing.
Extensive experience with popular deep learning frameworks such as TensorFlow, PyTorch, or similar.
Strong programming skills in Python and experience with performance profiling tools.
Ability to analyze complex data, draw meaningful conclusions, and communicate findings effectively.
Excellent problem solving skills and a proactive approach to identifying and resolving technical challenges.
A collaborative mindset and ability to thrive in a fast paced, globally distributed engineering environment.

What You'll Gain

The opportunity to make a tangible impact on the future of AI cloud infrastructure.
Work with cutting edge GPU hardware and advanced machine learning technologies.
Collaborate with an exceptional, diverse, and globally distributed team of engineers and researchers.
A fully remote, flexible work environment that values autonomy and results.
Continuous learning and professional development opportunities in a rapidly evolving field.
Competitive compensation and benefits package within a Nasdaq listed, growing company.