Applied Research Scientist

2 Hours ago • 6 Years +

Job Summary

Job Description

As an Applied Research Scientist at Pika AI, you will develop advanced AI tools using our foundation models. You will collaborate with researchers, designers, and engineers to create models for visual effects, character replacement, and style transformations, ensuring seamless integration into production environments. Responsibilities include developing video applications, designing data pipelines, and translating algorithms into user-friendly features. Requirements include experience in computer vision, machine learning, and AI models like diffusion models and GANs, along with strong engineering practices, proficiency in PyTorch, and expertise in data processing.
Must have:
  • 6+ years experience in computer vision or machine learning.
  • Experience with diffusion models, GANs, VAEs, or related AI models.
  • Experience with vision transformers.
  • Experience working on multi-modal video models.
  • Proficiency in PyTorch for data processing, model training, and deployment.
  • Experience developing applications based on foundational video models.
  • Expertise in large-scale data processing and dataset construction.
Good to have:
  • Solid coding abilities and a strong grasp of algorithm fundamentals.
  • Familiarity with distributed training tools like FSDP or DeepSpeed.

Job Details

We are seeking an Applied Research Scientist to join the Pika AI team. In this role, you will focus on developing advanced AI tools leveraging our foundation models.

You will collaborate closely with researchers, product designers, and engineers to develop models that deliver exceptional visual effects, character replacement, style transformations, and more, ensuring seamless integration into production environments.

Ideal candidates are passionate about cutting-edge applied AI techniques, including multi-modal video models, video super-resolution, conditional video generation, video editing, inpainting, and controllable generation.

Position Responsibilities

  • Develop innovative video applications, including controllable generation, video editing, and consistent character generation.
  • Design and build robust data pipelines essential for powering these applications.
  • Collaborate with product and design teams to translate state-of-the-art algorithms into user-friendly product features, enhancing the experience for tens of millions of users.

Position Requirements

  • 6 year+ experience working on computer vision, machine learning or related fields.
  • Demonstrated experience with diffusion models, GANs, VAEs, or other relevant AI models.
  • Direct experience working with vision transformers.
  • Experience working on multi-modal video models.
  • Strong engineering practices with proficiency in PyTorch, covering data processing, model training, and deployment workflows.
  • Hands-on experience developing applications based on foundational video models, including video inpainting, controllable generation, and human-centric modeling.
  • Proven expertise in large-scale data processing, dataset construction, and automated data cleaning.
  • (Optional) Solid coding abilities and a strong grasp of algorithm fundamentals; familiarity with distributed training tools such as FSDP or DeepSpeed is a plus.

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About The Company

We're revolutionizing video creation to be seamless and accessible for everyone. Our small, dynamic team values efficiency, collaboration, and creativity. We're seeking individuals with intellect, work ethic, and ambition to join us in breaking down barriers and making a real impact. Experience career growth in a culture that fosters both individual and collective development.Our headquarters are located in Palo Alto, CA.

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

Palo Alto, California, United States (On-Site)

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