Teleop Platform Engineer, Real-Time Systems & UI

Mecka AI; Toronto; On-site; CAD 90,000 - 130,000; Full time

Job summary

Mecka AI is building the data infrastructure layer for robotics and embodied AI. Our operators run robots across countries and oceans; you will own the link between them, delivering multiple camera streams to the operator and commands back to the robot with minimal delay, and recording data on-site and off-site too.

You will design and build real-time transport, optimize the latency budget, ensure robust connections, build the operator interface, and set up on-site recording and data storage

Qualifications

• 3+ years building production level real-time networked systems.
• Experience with low-latency media transport (WebRTC, RTP/SRTP, QUIC/UDP) and video encoding trade-offs.
• You've measured and reduced latency in a production system and can explain where the time went.
• Comfortable building a polished interface yourself, web or native.
• Strong in at least one of TypeScript, Go, Rust, C++, or Python; comfortable across client, server, and edge devices.
• Comfortable deploying and debugging software on remote Linux machines you can't physically touch.

Responsibilities

• Build the real-time transport between robot sites and operator stations: low-latency video, robot state, and control commands over the public internet.
• Own the end-to-end latency budget: instrument glass-to-glass and command-to-motion latency, optimize encoding, transport, routing, and jitter buffers.
• Make the link robust: NAT traversal, congestion and packet loss handling, bandwidth adaptation, reconnection signals.
• Design and build the operator interface: camera layouts, robot state/health, latency indicators, and fast workflows for starting/ending episodes.
• Build operator-facing tooling: queueing operators to robots across sites, session handoff, fleet visibility.
• Own on-site recording: capture synchronized streams and metadata, buffer locally, upload over constrained networks.
• Set up infrastructure for data storage and access of robot teleop episodes.

Skills

Real-time systems

Low-latency transport

Latency optimization

Programming languages

Tools

WebRTC

RTP/SRTP

QUIC/UDP

Job description

About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.
We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.
We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.

The role

Our operators control robots across countries and oceans. You'll own the link between them: getting multiple camera streams to the operator and commands back to the robot with as little delay and jitter as physics allows, and building the interface operators use all day. Because every byte you stream is also training data, you'll own recording it on-site and getting it reliably off-site too.

What you'll do

• Build the real-time transport between robot sites and operator stations: low-latency video (multiple cameras, possibly depth), robot state, and control commands over the public internet.

• Own the end-to-end latency budget. Instrument glass-to-glass and command-to-motion latency, find where every millisecond goes, and cut it: encoding settings, transport choice, routing, jitter buffers, relay placement.

• Make the link robust: NAT traversal, congestion and packet loss, bandwidth adaptation, reconnection, and clear signals to the operator and robot when quality degrades.

• Design and build the operator interface: camera layouts, robot state and health, task instructions, latency and connection indicators, and fast workflows for starting, labeling, and ending episodes.

• Build operator-facing tooling: queueing operators to robots across sites, session handoff, and basic fleet visibility.

• Own on-site recording: capture synchronized streams and metadata into a well-defined episode format, buffer locally, and upload reliably over constrained site networks.

• Set up the infrastructure for data storage and access of robot teleop episodes.

What we're looking for

• 3+ years building production level real-time networked systems: video streaming, video conferencing, cloud gaming, remote desktop, live broadcast, or similar.

• Hands-on experience with low-latency media transport (e.g., WebRTC, RTP/SRTP, QUIC/UDP-based protocols) and video encoding trade-offs.

• You've measured and reduced latency in a production system and can explain where the time went.

• Comfortable building a polished interface yourself, web or native, with good product instincts for people who use a tool eight hours a day.

• Strong in at least one of TypeScript, Go, Rust, C++, or Python; comfortable across client, server, and edge devices.

• Comfortable deploying and debugging software on remote Linux machines you can't physically touch.

Nice to have

• Experience with robotics, teleoperation, drones, or other remote-control systems.

• Hardware video encode/decode on edge devices; multi-camera synchronization.

• Built data pipelines that move large volumes of sensor or video data from the edge to cloud storage.

• Experience with global network deployment: relays/TURN, choosing regions, measuring paths between countries.

• Game development, VR/XR, or other latency-sensitive interaction design.

We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, we will partner with you to meet your needs.

We may use AI-assisted tools to help evaluate applications against the requirements of this role. These tools support our recruiting team in identifying qualified candidates but do not replace human judgment or limit which applications may be reviewed or considered.