Realtime Engineer, Multi-Modal AI

**About T4R Labs** T4R Labs is a deep tech lab building at the frontier of AI. We work on hard, unsolved problems where real-time performance, multi-modal understanding, and safety all have to hold up under production load — not just in a demo. **The Role** We're looking for an experienced realtime engineer to help us build systems that process and respond to audio, video, and text simultaneously, with the latency budgets of a live conversation rather than a batch job. You'll work at the intersection of low-latency infrastructure and multi-modal AI models, owning the pipelines that turn raw sensory streams into model inputs and model outputs into something a user experiences as instant. This is a hands-on, high-ownership role. You'll be contributing to architecture decisions, not just implementing someone else's spec. **What You'll Do** * Design and build low-latency, high-throughput pipelines for streaming audio, video, and text into and out of multi-modal models * Optimize end-to-end latency across the stack — networking, serialization, model inference, and rendering * Work closely with ML engineers to co-design model interfaces that are realtime-friendly (streaming inference, chunked generation, interruption handling, etc.) * Debug and eliminate jitter, dropped frames, and tail latency in production systems * Build the monitoring and tooling needed to keep a realtime system observable and reliable * Make pragmatic tradeoffs between quality, latency, and cost as the product scales **What We're Looking For** * 5+ years of experience building realtime or low-latency systems (e.g., video/voice conferencing, live streaming, gaming netcode, trading systems, or similar) * Strong systems programming skills (C++, Rust, Go, or similar) and comfort reasoning about performance at the network, OS, and hardware level * Experience with streaming protocols (WebRTC, RTP, gRPC streaming, or similar) * Familiarity with the practical constraints of serving ML models in production — batching, quantization, streaming inference * A track record of shipping systems that hold up under real user load, not just in benchmarks * Comfort working in a fast-moving, early-stage environment with ambiguous specs * Curious, entrepreneurial, and comfortable speaking your mind — we want people who'll push back on a bad idea, ours included * A self-starter who takes real ownership and accountability, but also works well as part of a small, close-knit team **Bonus points for:** * Direct experience integrating multi-modal (audio/video/text) AI models into a live product * Experience with GPU-accelerated inference serving (Triton, TensorRT, vLLM, or similar) * Prior work on voice assistants, live translation, or interactive AI agents **Why T4R Labs** * Work directly with the founding team on problems that don't have off-the-shelf solutions * High autonomy, high impact — your decisions ship * We're seed stage: this role is equity only for now, with salary starting once we close funding **Work Authorization & Background Check** You must be a U.S. citizen or otherwise authorized to work in the United States without employer sponsorship. As an early-stage company, we're not able to sponsor work visas at this time. Final offers of employment are contingent on successful completion of a background check. **How to Apply** Reach out with your resume and a note on the most interesting realtime system you've built.