Founding Deep Learning Researcher

  • US$170000 - US$250000 per annum
  • San Francisco, California
  • Permanent

Founding Deep Learning Researcher:

We are a pioneering AI startup that has recently secured Series A funding, aiming to redefine the landscape of digital media. Our primary focus is to revolutionize video storytelling through cutting-edge AI and generative models. We are seeking a Founding Deep Learning Research to build out our research efforts with this recent funding round.

As a Founding Deep Learning Researcher, your expertise will bridge the realms of computer vision and LLMs, pushing the boundaries of how stories are told in the digital age. Your role will be pivotal in conducting groundbreaking research, refining AI models for video interpretation and generation, and collaborating with our team to integrate advanced natural language understanding into visual contexts.

As you delve into the intricacies of video data and narrative structures, you'll ensure our solutions are both visually perceptive and linguistically coherent, championing ethical AI practices and setting new industry benchmarks.

What We Can Offer a Founding Deep Learning Researcher:

Joining us isn't just about being part of another startup. Here, you get:

  • Competitive Compensation: A competitive base salary complemented by a meaningful equity stake.
  • Early-stage Impact: As one of our pioneering members, your influence will ripple through every pixel of our product, shaping the AI video narrative realm.
  • Growth & Learning: With the dynamism of a startup and the support of our seasoned team, your growth will be exponential, both professionally and personally.
  • Flexibility & Balance: Enjoy flexible schedules and the potential for remote work. We value your well-being as much as your outputs.
  • Innovative Culture: Thrive in an environment that encourages risk-taking, innovation, and collaborative excellence.

Keywords: deep learning, machine learning, generative AI, artificial intelligence, 3D, 2D, image processing, graphics, computer vision, LLMs, large language models, video, imaging, openCV, openGL, python, GANS, generative adverserial networks, neural networks, CNNs, image editing, video generation, multi-modal learning, image restoration

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