Machine Learning Systems Engineer (Remote - EU)

We are seeking a talented Machine Learning Systems Engineer to join a remote-first, globally distributed team working on cutting-edge AI infrastructure. In this role, you will contribute to the development of large-scale language model systems, focusing on high-performance training, inference, and self-improving AI agents. You will work at the intersection of machine learning research, distributed systems, and high-performance computing, building tools and frameworks that enable researchers and organizations worldwide to deploy advanced AI solutions.

This role offers the chance to work on technically demanding, open-source projects while collaborating with a passionate international team. Your work will have a direct impact on the future of scalable AI systems. Accountabilities

• Contribute to the development and optimization of large-scale language model frameworks
• Implement high-performance distributed training algorithms using frameworks such as Megatron-LM, DeepSpeed, and vLLM
• Develop and optimize inference engines and tools for model deployment, fine-tuning, and AI agent self-improvement
• Integrate diverse machine learning ecosystems including HuggingFace and other LLM tools
• Optimize performance across multi-GPU, multi-node architectures, leveraging HPC and CUDA/ROCm programming
• Collaborate with the open-source community to enhance the codebase, implement features, and resolve issues
• Research and implement advanced techniques for self-improving AI agents and high-efficiency ML pipelines

• 3+ years of experience in machine learning engineering or research
• Proficiency in Python and C/C++, with strong systems programming skills
• Deep understanding of high-performance computing concepts, including MPI, BSP, and distributed multi-GPU training
• Solid experience with transformer architectures, gradient descent, backpropagation, and deep learning training
• Familiarity with distributed training strategies: data parallelism, model parallelism, pipeline parallelism
• Experience with containerization (Docker, Kubernetes) and cluster orchestration
• Demonstrated experience with ML frameworks like vLLM, Megatron-LM, HuggingFace, or similar
• Commitment to open-source development and community collaboration
• Excellent problem-solving, debugging, and performance optimization skills
• Bonus: Advanced degrees (MS/PhD), experience with SLURM, mixed-precision training, MLOps, or prior contributions to major open-source ML projects

• Competitive compensation including salary and equity participation
• Fully remote, work-from-anywhere flexibility
• Comprehensive global benefits including mental health support
• Open PTO policy and flexible working hours
• Paid parental leave and support for personal well-being
• Opportunities for continuous learning and professional development
• Regular team offsites, virtual events, and global gatherings to foster team collaboration
• Inclusive, transparent, and supportive culture prioritizing growth and knowledge-sharing