Senior Software Engineer, Inference

PikaPalo Alto, CA
$185,000 - $300,000Hybrid

About The Position

We are seeking a Senior Inference Engineer 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 technologies. Your expertise will drive significant improvements to model speed and efficiency, ensuring our creative AI systems deliver industry-leading user experiences at scale. You will design and optimize inference pipelines, implement state-of-the-art acceleration techniques, and work closely with researchers and engineers across the team to push the boundaries of what’s possible in real-time AI deployment. Your efforts will play a foundational role in powering the next generation of Pika’s video and language models.

Requirements

  • 5+ years engineering experience, with a strong track record in inference acceleration and model deployment at scale.
  • Proven expertise in inference optimization, including quantization, attention acceleration, and deep learning compiler stacks.
  • Deep knowledge of GPU programming (CUDA, NCCL) and experience with SP, TP, PP, and other forms of parallelism for distributed inference.
  • Familiarity with video generation (videogen) models and large language models (LLMs).
  • Strong cross-discipline communication skills; able to drive shared goals across research and engineering functions.
  • Self-driven, solutions-oriented, and capable of managing ambiguity in a fast-paced startup environment.

Nice To Haves

  • Experience with high-throughput video or real-time streaming model deployment
  • Familiarity with distributed training and optimization toolkits
  • Contributions to open source projects in AI infrastructure or deep learning compilers
  • Startup or rapid prototyping experience

Responsibilities

  • 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.
  • Technical Excellence: Drive rigorous code reviews, participate in technical discussions, and mentor fellow engineers on best practices in inference and GPU programming.

Benefits

  • Competitive salary in the AI industry
  • Equity in a fast-growing startup shaping the future of AI
  • Comprehensive health benefits, monthly stipends, company retreats
  • A supportive and collaborative office culture—we’re all building and launching together
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