Founding Engineer - AI

We are a funded, stealth mode AI hardware startup in Long Beach, and we are hiring our first engineer.

We capture a person in our studio, their voice, their face, how they move, and how they actually think, then compress all of that down into something small enough to run on a device you can hold in your hand with no internet connection. That device then brings them to life on real hardware.

Offline is not a privacy feature we added on. It is the product. Nothing leaves the device. No third party APIs, no cloud inference, no sending anyone’s voice out to a vendor. Everything is ours and everything runs local.

We are backed by a single investor with a $20M commitment, our patent is finalized, and our capture studio is already built out with a six camera 360 rig, high definition facial capture, and studio grade audio. What we do not have yet is the engineer who turns all of that captured data into a working system. That is this job.

Why join us?

• You are employee number one. Not early, first. You will pick the stack, set the architecture, and set the engineering standards for everyone we hire after you.
• Nothing is decided yet. No database chosen, no stack locked in, no legacy code to inherit. If you have ever wanted to make the calls instead of living with someone else’s, this is that seat.
• Funded and stable. The heavy capital spend is already behind us.
• Milestone bonus tied to launch.
• Work nobody has a playbook for. You would be writing it., You will own the full path from raw data to a working AI system running on constrained hardware. That includes:
• Building the data pipeline from the ground up, moving large volumes of raw capture data into a local database and getting the schema right
• Standing up the training and dev staging environment and running training against that data
• Selecting and deploying a small language model that runs locally on NVIDIA Jetson class hardware, and getting it to perform inside real memory and thermal budgets
• Hardware bring up and the integration layer between the model and the physical device
• Setting engineering standards and helping hire the next three engineers on the team

• Strong Python, and comfortable dropping into C++ or C when the runtime demands it
• Real data engineering experience, pipelines, ETL, schema design, moving large and messy data reliably
• Hands on running LLMs or SLMs locally rather than through a cloud API. Model selection is a collaborative call and we want your opinion
• Database fluency, SQL, PostgreSQL, MySQL, SQLite or MongoDB. We have not picked one yet, so we care that you have opinions more than which one you have used
• Linux systems fluency, ideally including ARM, ARM64 or embedded Linux
• Docker and containerized deployment
• You have owned a project end to end without a spec, and you know when to prototype versus when to build it properly
• You can handle sensitive personal data with the seriousness it deserves. That trust is the company

Strongly preferred, we do not expect all of these

• NVIDIA Jetson experience, JetPack, TensorRT or CUDA on embedded
• Speech systems, ASR, voice cloning, streaming TTS or real time audio
• Fine tuning, quantization or distillation of small models, synthetic data generation
• Multi camera capture rigs, camera sync, photogrammetry, motion capture or performance capture
• A visual effects, animation or video game background. If you have built 3D or capture pipelines, that crossover is genuinely valuable here
• Computer vision, robotics or holographic imaging