Member of Technical Staff, Multimodal

Hark

• $180K — $450K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in leading neural network research.
  • Strong expertise in data-driven experimentation and iterative model debugging.
  • Proficiency in building large-scale distributed machine learning systems.
  • Ability to take ownership and drive projects to successful completion.

Responsibilities

  • Drive research to enhance real-time multimodal intelligence capabilities.
  • Develop data filtering and synthetic data generation techniques for multimodal training.
  • Create evaluation frameworks to assess model capability and user experience.
  • Design algorithms for state-of-the-art multimodal foundation models.
  • Collaborate with product and engineering teams to implement research advances.

Benefits

  • Opportunity to work on cutting-edge multimodal AI technology.
  • Collaborative team environment with opportunities for cross-disciplinary learning.
  • Involvement in product integration for real-world AI applications.
Full Job Description
About the Role

The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, and vision. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences.

As part of the Omni team, you will help drive the development of real-time audio, video, and multimodal world models. This includes working across the full stack-from data and modeling to training, serving, and product integration. You will contribute to both pretraining and posttraining efforts while collaborating closely with product teams to push the boundaries of model capability and deliver exceptional end-to-end user experiences.

Responsibilities
  • Drive research and development agendas to advance real-time multimodal intelligence, including audio, video, and world modeling capabilities.
  • Improve data quality for large-scale multimodal training by developing data filtering, curation, and synthetic data generation techniques.
  • Build evaluation frameworks and internal benchmarks to measure model capability, reliability, and user experience across modalities.
  • Design and implement efficient algorithms and training strategies to achieve state-of-the-art performance in multimodal foundation models.
  • Collaborate closely with product and engineering teams to translate research advances into impactful, real-world AI experiences.

Requirements
  • Proven track record of leading research that significantly improves neural network capability through advances in data, modeling, or training.
  • Strong experience in data-driven experimentation, systematic analysis, and iterative model debugging.
  • Experience building or working with large-scale distributed machine learning systems.
  • Strong ownership mindset and willingness to do whatever is necessary to deliver the best end-to-end AI user experience.

Bonus Qualifications
  • Background in graphics engines, simulation, or rendering techniques is a plus.
  • Experience with multimodal models, speech/audio systems, video models, or real-time AI systems is a strong plus.

Compensation

The US base salary range for this full-time position is between $180,000 - $450,000 annually.

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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