Senior ML Engineer for Large-Scale Foundation Models

Jobgether; Germany (OH); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Competitive compensation

International environment

High ownership

Job summary

Jobgether is seeking an experienced AI infrastructure engineer to work on the cutting edge of foundation models and ML systems. You will help build inference and fine-tuning technologies for large-scale AI platforms, focusing on quality, efficiency, and scalable deployment.

You will collaborate with researchers and engineers in a fast-moving, international environment, applying strong software engineering practices and contributing to the evolution of AI infrastructure.

Qualifications

• Deep understanding of ML foundations and reinforcement learning.
• Strong expertise in modern DL techniques for language processing and generation.
• Experience training large ML models across multiple compute nodes.
• Solid understanding of performance optimization for large neural networks, including sharding and custom kernels.
• Strong Python programming and software engineering skills.
• Extensive experience with modern DL frameworks, especially JAX.
• CI/CD, version control, unit testing, production-grade practices.

Responsibilities

• Develop and improve fine-tuning methodologies for foundation models (LoRA-based and full-parameter).
• Optimize model quality and training efficiency across large-scale ML workloads.
• Address bottlenecks in LLM inference to improve production performance and resource use.
• Build training and evaluation pipelines using JAX with advanced inference techniques.
• Experiment with model architectures including dense and mixture-of-experts models.
• Develop scaling laws to guide model development and resource allocation.
• Investigate low-precision training/inference approaches (FP8, MXFP4, etc.).
• Work with distributed training environments across multiple GPU clusters.
• Analyze performance factors like sharding, custom kernels, hardware capabilities.
• Translate research into robust, scalable, production ML systems.

Skills

LoRA fine-tuning

Full-parameter tuning

Distributed training

Python

JAX

Model optimization

Inference optimization

Hardware utilization

Speculative decoding

Multi-node training

Job description

Jobgether is seeking an experienced AI infrastructure engineer to work on the cutting edge of foundation models and ML systems. You will help build inference and fine-tuning technologies for large-scale AI platforms, focusing on quality, efficiency, and scalable deployment.

You will collaborate with researchers and engineers in a fast-moving, international environment, applying strong software engineering practices and contributing to the evolution of AI infrastructure.