Senior ML Engineer (Token Factory)

Meyandy LLC; Berlin; Hybrid; EUR 110.000 - 150.000; Vollzeit

Benefits dieser Stelle

Competitive compensation

Career growth and learning oppor tunun

Flexible working arrangements

Zusammenfassung

Nebius in Berlin is seeking a Senior ML Engineer for the Token Factory to push the performance of a high‑throughput AI inference and fine‑tuning platform. You will tackle bottlenecks, design GPU‑level optimizations, and collaborate with an expert team of engineers.

Ideally you have deep knowledge of transformer architectures, vast experience with PyTorch, CUDA tooling, and building scalable distributed systems. English communication and leadership are valued in this dynamic startup environment.

Qualifikationen

• Profound understanding of ML theory and transformer architectures.
• Experience profiling GPU workloads with Nsight, PyTorch profiler, or similar.
• Knowledge of GPU memory hierarchy and compute/memory tradeoffs.
• Familiarity with LLM concepts such as MHA, RoPE, KV-cache, Flash Attention, and quantisation.
• Experience with large neural network training and sharding strategies.
• Strong software engineering with Python.
• Experience with CI/CD, version control and unit testing.
• Strong communication and leadership abilities.

Aufgaben

• Build and improve high‑performance inference and fine‑tuning platform.
• Optimize throughput, latency and cost‑per‑token across GPUs.
• Collaborate with cross‑functional teams and contribute to core research.
• Implement novel speculative decoding architectures and related tooling.
• Contribute to open‑source inference engines and low‑precision pipelines.

Kenntnisse

Python

Machine learning

PyTorch

GPU profiling

Distributed systems

CI/CD

Leadership

English communication

Tools

Nsight

CUDA

Triton

CUTLASS

Jobbeschreibung

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 supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

The role

Token Factory is a part of Nebius Cloud, one of the world's largest GPU clouds, running tens of thousands of GPUs. We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.

Some directions we are currently working on, and which you can be a part of:

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
• Inference engines support: Implement novel speculative decoding architectures, optimisecomponents of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
• Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and transformer architecture.
• Experience profiling GPU workloads using Nsight, PyTorch profiler, or similar tools
• Understanding of GPU memory hierarchy and compute/memory tradeoffs
• Familiarity with important ideas in LLM space, such as MHA, RoPE, KV-cache, Flash Attention, and quantisation
• Understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)
• Strong software engineering skills (we mostly use Python)
• Deep experience with modern deep learning frameworks
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
• Strong communication and leadership abilities

Nice to have:

• Experience working with open-source inference engines (vLLM, SGLang, TensorRT-LLM), including contributions
• Experience with kernel languages or DSLs such as Triton, Cute, CUTLASS, CUDA
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess
• Excellent command of the English language, alongside superior writing, articulation, and communication skills.

Benefits & Perks:

• Competitive compensation
• Career growth and learning opportunities
• Flexibi… Senior ML Engineer (Token Factory) — Nebius, Berlin.