3mo ago
$250K – $350K/yr

ML Engineer, Inference & Optimization

Palo Alto Hqfull-timemid
Machine Learning EngineerData
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Quick Summary

Key Responsibilities

Lead and implement advanced inference acceleration techniques, including attention optimization and quantization for efficient model serving.

Technical Tools
Machine Learning EngineerData

About the Role

~1 min read

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.

 

Responsibilities

~1 min read
  • →

    Accelerate Inference: Lead and implement advanced inference acceleration techniques, including attention optimization and quantization for efficient model serving.

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    Maximize GPU Parallelism: Engineer and optimize GPU strategies across tensor, sequence, and pipeline parallelism (TP, SP, PP) for maximal efficiency and scalability.

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    Programming for Performance: Develop and optimize high-performance computing kernels and distributed workloads using CUDA and NCCL.

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    Advance AI Deployment: Collaborate with research and engineering teams to bring state-of-the-art videogen and large language models into production.

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    Improve Training Efficiency: (Bonus) Contribute to improvements in model training speed, stability, and resource utilization as part of our deployment lifecycle.

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    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.

 

Nice to Have

~1 min read
  • 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

~1 min read
✓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.

Location & Eligibility

Where is the job
Palo Alto Hq
On-site at the office
Who can apply
Same as job location

About this job

Pay per year
$250,000–$350,000 a year
43% above the $210,000 median for Machine Learning Engineer jobs on Jobera (869 salaries).
Posted
118 days ago
Employer
has 15 open jobs on Jobera.

Listing Details

Posted
June 23, 2026
First seen
September 25, 2026
Last seen
October 18, 2026

Posting Health

Days active
22
Repost count
0
Trust Level
32%
Scored at
October 18, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
Employees
51-200
Domain
View company profile
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ML Engineer, Inference & Optimization$250K – $350K