Member of Technical Staff, Multimodal
Hark
$180,000 - $450,000 / year
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Description
About Hark
Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.
We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.
To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.
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.
About this role
Hark's Omni team is developing multimodal AI systems that process and generate content across audio, video, and text in real time. As a Member of Technical Staff, you'd work across the full stack—from data curation and model training to serving and product integration—while collaborating with product teams to turn research advances into working AI experiences. The role spans both foundational research and practical deployment, so you'd need comfort moving between theoretical improvements and real-world implementation.
This position calls for someone with a demonstrated history of shipping research that meaningfully advances neural networks, whether through data innovation, modeling breakthroughs, or training strategies. You should have hands-on experience with large-scale distributed ML systems and a systematic approach to experimentation and debugging. The company values ownership and pragmatism—a willingness to do whatever's needed to deliver end-to-end experiences that work. Prior work in multimodal systems, speech, video, or real-time AI is valuable; background in graphics, simulation, or rendering is a bonus.
The role is full-time and in-office in San Jose, with a base salary range of $180,000 to $450,000 depending on experience and skills.
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Pay for this role
$180,000 to $450,000 per year
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