ML Systems Engineer at NexusAM

Jack & Jill; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

NexusAM is a seed-stage Imperial College London spinout building an AI inference layer for metal 3D printing. You will deploy and optimize multi-modal inference pipelines to provide real-time quality insights for safety-critical components.

Join a tight-knit team of eight, work with C++, ONNX Runtime and TensorRT to compress testing timelines and deliver reliable edge AI deployments with meaningful equity in a deep-tech startup backed by top investors.

Qualifications

• Has 3+ years of experience deploying real-world AI systems with CNNs, time-series models and transfer learning.

Responsibilities

• Build and optimize high-performance, multi-modal data processing and inference pipelines for images, time-series data, and complex point clouds.
• Deploy large-scale deep learning models into resource-constrained environments using C++ frameworks like ONNX Runtime, TensorRT, or libtorch.
• Collaborate with the software team to implement novel computational approaches that ensure strict latency budgets and edge-scale hardware reliability.

Skills

C++ for ML inference

CNNs

Time-series models

Transfer learning

Tools

ONNX Runtime

TensorRT

libtorch

CUDA

Job description

Job Title

ML Systems Engineer

Salary

Not Disclosed

Company Description

NexusAM is a seed-stage Imperial College London spinout building an AI intelligence layer for metal 3D printing, transforming multi-modal sensor data into real-time quality assurance for aerospace, defence, and medical manufacturers.

Job Description

As an ML Systems Engineer at NexusAM, you will deploy and optimize multi-modal inference pipelines for safety-critical metal 3D printing. Working in a tight-knit team of eight, you’ll tackle research-grade deployment challenges using C++, ONNX, and TensorRT to provide real-time insights that replace days of destructive testing for aerospace and medical components.

Location

London, UK

Why this role is remarkable

• Join an elite team of eight experts spun out from Imperial College London, working at the bleeding edge where AI meets advanced safety-critical manufacturing.
• Solve high-stakes engineering problems by compressing days of X-ray CT and destructive testing into real-time quality assurance insights for global manufacturers.
• Gain significant impact as an early team member with meaningful equity in a seed-stage startup backed by leading investors in the deep-tech space.

What You Will Do

• Build and optimize high-performance, multi-modal data processing and inference pipelines for images, time-series data, and complex point clouds.
• Deploy large-scale deep learning models into resource-constrained environments using C++ frameworks like ONNX Runtime, TensorRT, or libtorch.
• Collaborate with the software team to implement novel computational approaches that ensure strict latency budgets and edge-scale hardware reliability.

The ideal candidate

• Has 3+ years of experience deploying real-world AI systems, with a deep understanding of CNNs, time-series models, and transfer learning.
• Possesses professional proficiency in C++ for ML inference and experience with frameworks like TensorRT, libtorch, or GPU programming (CUDA).
• Demonstrates a bias toward practical, maintainable solutions and is eligible to work in the in-person London office without visa sponsorship.