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 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.

• Hands-on experience with large language models or other complex AI architectures.

• 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

• Flexible working hours

• Join a dynamic start-up and a rapidly growing team

• Work with international industry and science experts

• Take on responsibility and shape our company and technology

• Regular team events