ML Engineer, Inference & Optimization
At a glance
Mid-level Machine Learning Engineering role at Pika. Remote, United States · full-time · $250,000–$350,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Speed up model serving with attention improvements and quantization
- Tune tensor, sequence and pipeline parallelism to use GPUs efficiently at scale
- Build and optimize performance-focused kernels and distributed workloads with CUDA and NCCL
- Bring video-generation and large language models into production with research and engineering teams
- Review code, guide fellow engineers and contribute to technical decisions on inference and GPU programming
What you bring
- At least five years of engineering work, including a strong record in inference acceleration and large-scale model deployment
- Hands-on command of inference optimization, including quantization, faster attention and deep learning compiler stacks
- Deep GPU programming knowledge with CUDA and NCCL, plus distributed inference experience using sequence, tensor or pipeline parallelism
- Familiarity with video-generation models and large language models
Who this fits
This role suits a mid-career engineer ready to take on technically demanding inference and GPU optimization work, with collaboration across research and engineering. The posting describes the position as senior or staff level. You’ll work from the Palo Alto office three to five days a week.
From the employer
About the Role
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.
What You’ll Do
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.
What We’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.
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.
Nice to Have
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
What We Offer
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
About Pika
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.