ML Engineer, Inference & Optimization

Job summary

Responsibilities

We are seeking Senior/Staff level Inference Engineers to accelerate the performance of Pika's AI-driven products. In this highly technical role, you will operate at the intersection of cutting-edge inference acceleration, GPU parallelism, advanced model deployment, and video generation…

• Accelerate Inference: Lead and implement advanced inference acceleration techniques, including attention optimization and quantization for efficient model serving.
• Maximize GPU Parallelism: Engineer and optimize GPU strategies across tensor, sequence, and pipeline parallelism (TP, SP, PP) for maximal efficiency and scalability.
• Programming for Performance: Develop and optimize high-performance computing kernels and distributed workloads using CUDA and NCCL.
• Advance AI Deployment: Collaborate with research and engineering teams to bring state-of-the-art videogen and large language models into production.
• Improve Training Efficiency: (Bonus) Contribute to improvements in model training speed, stability, and resource utilization as part of our deployment lifecycle.

What they're looking for

• Experience: 5+ years engineering experience, with a strong track record in inference acceleration and model deployment at scale.
• Inference Mastery: Proven expertise in inference optimization, including quantization, attention acceleration, and deep learning compiler stacks.
• GPU & Parallelism: Deep knowledge of GPU programming (CUDA, NCCL) and experience with SP, TP, PP, and other forms of parallelism for distributed inference.
• AI Domain Knowledge: Familiarity with video generation (videogen) models and large language models (LLMs).
• Collaboration: Strong cross-discipline communication skills; able to drive shared goals across research and engineering functions.

Tech stack

• CUDA