Observability & DevOps Engineer—Robotic Imaging

NeuroTech X; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

Vexev is redefining medical imaging with robotic ultrasound, real-time software, and ML-powered insights. We seek a hands-on DevOps/Observability Engineer to scale our autonomous robotic imaging system.

You will build end-to-end observability, collect telemetry, and improve deployment visibility across testing, staging, and clinical use, driving reliability and fast root-cause analysis in a fast-moving environment.

Qualifications

• Strong background in deploying and maintaining reliable systems.
• Experience building observability and monitoring across distributed systems.
• Ability to translate telemetry into actionable improvements.

Responsibilities

• Build observability across robotic imaging systems, test rigs, cloud services, deployment pipelines, and internal tools.
• Collect telemetry, logs, metrics, and traces to help engineers diagnose root causes.
• Create dashboards, alerts, and workflows to visualize reliability and performance.

Skills

DevOps expertise

Observability

Reliability engineering

Tools

Grafana

Prometheus

Loki

Tempo

OpenTelemetry

Datadog

CloudWatch

AWS

Job description

DevOps/Observability Engineer, Robotics

Have you ever wondered why medical imaging still feels so constrained, despite decades of technological progress? Sensors are cheaper, computing is dramatically faster, and machine learning is changing what software can do. Yet in many areas of healthcare, clinicians still face the same trade-off: large, expensive systems for high-quality imaging, or ultrasound scans that depend heavily on scarce expert operators.

Vascular imaging is one of the clearest examples. The vessels that matter can be only a few millimetres wide. They move with the patient, change with pressure and physiology, and require real precision to assess reliably.

At Vexev, we are building a new category of vascular imaging. Our robotic ultrasound system combines advanced hardware, real-time software, machine learning, and clinical insight to create high-quality, operator-independent datasets at the point of care.

This is a hard systems problem. We are turning raw ultrasound and robotic sensing into clinically useful outputs, from image acquisition and processing through to visualisation, reporting, and analysis. The goal is simple: bring breakthrough imaging technology into real-world clinical use.

We have already deployed our system in a US clinical trial with near-perfect results, and are now progressing through FDA submission with major partnerships forming.

We are looking for a DevOps and Observability Engineer to help scale our autonomous robotic imaging systems. This person will work across telemetry, logs, metrics, traces, test systems, cloud infrastructure, and fleet monitoring to ensure observability and reliability in the real world.

About The Role

This is a hands-on engineering role for someone who wants to work close to the system. You will help build the infrastructure and operational workflows that allow us to understand how our robotic imaging system behaves across testing, deployment, and clinical use.

You will work with the engineering teams to make our systems more observable from end to end. That means collecting the right telemetry, structuring logs, building useful metrics, tracing important workflows, setting up alerts, improving deployment visibility, and helping engineers find root causes faster. You will also work with test systems and internal infrastructure to make sure we can measure reliability before systems reach the field.

This role could suit someone with a few years of strong experience who is ready to take on more ownership, or someone more senior who has already helped build observability and reliability practices in complex systems. We care less about exact years of proven experience and more about whether you are technical, curious, pragmatic, and able to make robotic systems easier to understand – especially as our fleet grows.

Your Work Will Include:

• Building and improving observability across robotic imaging systems, test rigs, cloud services, deployment pipelines, and internal tools.
• Working with telemetry, logs, metrics, and traces to help engineers understand system behaviour and diagnose root causes.
• Creating dashboards, alerts, and reporting workflows that make reliability, performance, and operational issues visible and actionable.
• Helping define what should be measured across a fleet of robotic systems, including system health, scan performance, software reliability, hardware behaviour, connectivity, and operational trends.
• Supporting cloud infrastructure, deployment workflows, CI/CD, logging pipelines, OTA updates and data infrastructure where needed.
• Contributing to future reliability intelligence, including anomaly detection, predictive monitoring, and ML-assisted fleet insights.
  

What We’re Looking For:

• Strong technical fluency across DevOps, observability, infrastructure, systems engineering, or production software operations.
• Comfort debugging complex systems where the root cause may sit across robotics, software, infrastructure, hardware, networking, configuration, data, or user workflow.
• A pragmatic approach to reliability: you care about robust systems, but you also know how to prioritise, sequence, and build what is useful first.
• Strong communication skills, especially the ability to turn noisy technical signals into clear explanations and actions.
• Curiosity about how systems behave in the real world, not just how they are expected to behave in design documents.
• Comfort working in ambiguity, asking good questions, and building structure where none exists yet.
• A bias toward ownership. When something is hard to understand, you help make it visible. When something fails repeatedly, you help make it diagnosable. When something matters to reliability, you help make it measurable.

You’ll Likely Have Experience With:

You do not need all of these, but experience in any of the following would be valuable:

• Observability platforms such as Grafana, Prometheus, Loki, Tempo, OpenTelemetry, Datadog, CloudWatch, or similar tools.
• Cloud infrastructure, especially AWS or similar cloud platforms.
• Linux systems, networking, containers, deployment pipelines, CI/CD, infrastructure-as-code, OTA updates, or production operations.
• Telemetry pipelines, structured logging, time-series data, distributed tracing, or operational analytics.
• Hardware-adjacent systems, robotics, instrumentation, medical devices, industrial automation, IoT, edge computing, or embedded systems.
• Test infrastructure, test rigs, reliability testing, system validation, or production support for complex technical products.
• Data systems, internal tools, APIs, databases, or full-stack software environments.
• Machine learning, anomaly detection, predictive maintenance, or operational intelligence.
• Medtech, healthtech, or another regulated, safety-conscious, quality-managed environment.

Working at Vexev

Work that matters.
We’re building the next generation of vascular imaging, helping healthcare move from reactive treatment to proactive care.

Hard problems, real-world impact.
You’ll help bring together robotics, ultrasound, machine learning, and clinical insight into technology that works where it matters most.

Autonomy with ownership.
You’ll be trusted with real responsibility, expected to solve meaningful problems with clear ownership and accountability for your high impact work.

Built for people who like the hard stuff.
This work is hard, but that’s the point. We’re building technology that could meaningfully improve how vascular disease is detected, monitored, and managed.

A workplace without the noise.
No dress code, no pointless meetings, flexible start and finish times, and a Surry Hills HQ designed for deep work, collaboration, and team lunches on the rooftop.

Before you go.

At Vexev, we hire people, not just skill sets. If you’re fired up about our mission and believe you could be outstanding in this role despite missing a few of the “requirements”, please apply. We value directness, clarity, and honest feedback, and we bring that same approach to hiring: every application is read by our team, never filtered by automation, and we aim to keep the process quick, human, and transparent.

We make hiring decisions based on your skills, experience, curiosity and passion. Here, we value and celebrate the diversity of perspectives, expressions and social and ethnic backgrounds. We deeply believe that these are key to creating a great place to work, and building an imaging device that is truly accessible to all.

Please complete our application form and we’ll be in touch with next steps! If you have any questions before you apply, feel free to email: [e-mail]

Application form

Tagged as: Embedded, Engineering, Hardware, Machine Learning, Software