A natural match if you have experience deploying AI models on edge hardware and collaborating across cross-functional teams.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Trener via Ashby
ABOUT US
Help make physical AI a reality.
At Trener Robotics, we are building the future of industrial automation through intelligent agents that understand natural language and control robotic stations. Our product, Acteris, bridges AI and robotics to deliver flexible, user-friendly automation.
We are a fast-growing, venture-backed company entering a phase of rapid scale. Our mission is to make AI-powered robotics accessible, and we are looking for a Senior AI Compute Engineer to own the deployment and execution of complex models across our physical edge hardware.
YOUR MISSION
Own the compute software stack that enables our robots to process heavy AI workloads and real-time control algorithms seamlessly at the edge. You will deeply understand the underlying hardware to build software that extracts maximum performance from it, without being responsible for hardware design itself. You will actively collaborate with and support the external partners designing our compute platforms. In this role, you will own outcomes for a critical product area, bringing structured judgment to complex problems as you bridge the gap between theoretical model performance and physical, real-world deployment.
KEY RESPONSIBILITIES
- Design software systems spanning multiple services to run Physical AI processes across heterogeneous architectures (CPU, GPU, NPU, FPGA).
- Build, optimize, and test software pipelines for deploying neural networks, large language models (LLMs), vision transformers, VLMs, and VLAs directly to edge devices.
- Deploy and accelerate deterministic robotics algorithms, ensuring they meet strict real-time execution constraints alongside machine learning workloads.
- Set code quality standards for the team and design test strategies for entire features, ensuring that your definition of "done" means it works on the floor, not just in CI.
- Drive alignment across cross-functional teams by proactively coordinating handoffs across roles (e.g., firmware, software, deployment) instead of waiting to be looped in.
- Plan across projects with clarity and confidence, breaking large initiatives into independently shippable increments and flagging schedule risk early.
- Push back on requirements that seem technically infeasible and run scoped spikes to de-risk hard problems rather than just flagging concerns.
WHAT WE ARE LOOKING FOR
- Proven experience working with state-of-the-art algorithms used in autonomous systems or advanced robotics.
- Proven experience deploying complex algorithms onto embedded and edge devices (specifically beyond standard laptops and desktop PCs).
- Deep understanding of hardware execution models (e.g., memory hierarchies, compute pipelines) to write software that maximally exploits the underlying compute and anticipates bottlenecks.
- Experience accelerating workloads on CPUs, GPUs (e.g., CUDA, TensorRT, ROCm) or FPGAs.
- Familiarity using Altera's Quartus and/or AMD's Vitis.
- Strong proficiency in writing production-grade, highly optimized C++ and Python.
Particularly strong candidates will have:
- An understanding of robot kinematics (forward and inverse), numerical optimization, and constraint-based programming.
- Knowledge of the inner workings of modern AI models and their specific hardware requirements.
- A background in electronics engineering to effectively interface software with edge hardware.
WHAT YOU WILL GET
- Ownership of the AI compute software layer for a category-defining automation platform.
- The opportunity to work hands-on with real robots and cutting-edge edge compute hardware from day one.
- Collaboration with a high-caliber team across AI, robotics, systems engineering, and product.
- A fast-moving, mission-driven environment where rigorous engineering and research-informed thinking are equally valued.
Source: Trener careers (Ashby)