ML Engineer Inference and Optimization
Pika is an active AI creative platform for generating and editing video, images, and audio, with a creator-facing app and an API offering.
Funding history
About Pika
Pika, operated by Mellis, Inc., provides a generative-AI platform through its websites, mobile apps, APIs, and third-party platforms. Its current product covers video, image, and audio creation/editing and offers access to first-party Pika and third-party models through an aggregated API platform.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will accelerate and optimize AI inference pipelines for video and language models. You will implement attention optimization, quantization, GPU parallelism, high-performance CUDA and NCCL workloads, and production deployments. You will contribute to code reviews, technical discussions, mentoring, and, optionally, training-efficiency improvements.
Requirements
- 5+ years of engineering experience
- Inference acceleration and model deployment experience at scale
- Inference optimization expertise, including quantization, attention acceleration, and deep learning compiler stacks
- GPU programming knowledge, including CUDA and NCCL
- Distributed inference parallelism experience, including SP, TP, and PP
- Familiarity with video-generation models and large language models
- Cross-disciplinary communication skills
Responsibilities
- Lead and implement inference acceleration techniques, including attention optimization and quantization
- Engineer and optimize tensor, sequence, and pipeline parallelism for distributed inference
- Develop and optimize high-performance kernels and distributed workloads using CUDA and NCCL
- Deploy video-generation and large language models into production
- Contribute to model training speed, stability, and resource-utilization improvements
- Drive code reviews, technical discussions, and mentoring on inference and GPU programming
Benefits
- Equity
- Comprehensive health benefits
- Monthly stipends
- Company retreats