AI Inference Engineer - Large Language Models (f/m/d)

fulltime

Employment Information

Overview:

You will join our product team in a position that sits at the intersection of artificial intelligence research and real-world solutions. We foster a highly collaborative work culture where you can expect to work closely with your teammates and have a high level of communication between teams through methodologies such as pair or mob programming.


Your responsibilities:

  • Model Inference: Focus on inference optimization to ensure rapid response times and efficient resource utilization during real-time model interactions.

  • Hardware Optimization: Run models on various hardware platforms, from high-performance GPUs to edge devices, ensuring optimal compatibility and performance.

  • Experimentation and Testing: Regularly run experiments, analyze outcomes, and refine the strategies to achieve peak performance in varying deployment scenarios.

  • Staying up to date with the current literature on MLSys


Your profile:

  • You care about making something people want. You want to ship something that will bring value to our users. You want to deliver AI solutions end-to-end and not finish building a prototype.

  • Bachelor's degree or higher in computer science or a related field.

  • You understand how multimodal transformers work.

  • You understand the characteristics of LLM inference (KV caching, flash attention, and model parallelization).

  • You have hands-on experience with large language models or other complex AI architectures.

  • You have experience in system design and optimization, particularly within AI or deep learning contexts.

  • You are proficient in Python and have deep understanding of deep learning frameworks such as PyTorch.

  • A deep understanding of the challenges associated with scaling AI models for large user bases.

Nice if you have:

  • Previous experience in a high-growth tech environment or a role focused on scaling AI solutions.

  • Expertise with CUDA and Triton programming and GPU optimization for neural network inference.

  • Experience with Rust.

  • Experience in adapting AI models to suit a range of hardware, including different accelerators.

  • Experience in model quantization, pruning, and other neural network optimization methodologies.

  • A track record of contributions to open-source projects (please provide links).

  • Some Twitter presence discussing ML Sys topics.


What you can expect from us:

  • Become part of an AI revolution!

  • 30 days of paid vacation

  • Access to a variety of fitness & wellness offerings via Wellhub

  • Mental health support through nilo.health

  • Substantially subsidized company pension plan for your future security

  • Subsidized Germany-wide transportation ticket

  • Budget for additional technical equipment

  • Flexible working hours for better work-life balance and hybrid working model

  • Virtual Stock Option Plan

  • JobRad® Bike Lease


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