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 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.
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.
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.
Ownership Mindset: Self-driven, solutions-oriented, and capable of managing ambiguity in a fast-paced startup environment.
Bonus: Experience in enhancing training efficiency, stability, or resource optimization for large models.
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
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
At Pika, we're crafting a future where video creation is seamless, intuitive, and universally accessible. Our mission is to empower creativity by breaking down technical barriers using the transformative power of AI. We’re a tight-knit, energetic team based in Palo Alto, CA, valuing efficiency, curiosity, and the ambition to make a meaningful impact on the world.
We work from our Palo Alto office 3–5 days a week and welcome applicants who are eager to contribute onsite.
Based on 576 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $205K/year, with most offers between $167K and $242K (10th–90th percentile: $132K–$276K).
This posting lists $185K–$250K, in line with the $205K market median.
See the full AI Engineering salary breakdown →