Asks for

The ad says“Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning”
The ad says“Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning”
The ad says“In this role, you will apply machine learning, data science, and advanced analytical techniques to complex challenges across the electromagnetic environment. Working within Metrea’s Decision Science Laboratory (DESLAB) and automated Solution Engine, you will design, test, and deploy ML-enabled capabilities that go beyond traditional signal processing approaches. This includes exploring the potential of methods such as Transformers, self-supervised learning, probabilistic modelling and simulation-driven learning approaches for electromagnetic sensing and exploitation. You will be successful if you are comfortable moving between research, experimentation, and operational delivery, turning ambiguous Defence and Aerospace problems into robust technical solutions that can be tested, explained, and deployed in real-world settings.”
The ad says“In this role, you will apply machine learning, data science, and advanced analytical techniques to complex challenges across the electromagnetic environment. Working within Metrea’s Decision Science Laboratory (DESLAB) and automated Solution Engine, you will design, test, and deploy ML-enabled capabilities that go beyond traditional signal processing approaches. This includes exploring the potential of methods such as Transformers, self-supervised learning, probabilistic modelling and simulation-driven learning approaches for electromagnetic sensing and exploitation. You will be successful if you are comfortable moving between research, experimentation, and operational delivery, turning ambiguous Defence and Aerospace problems into robust technical solutions that can be tested, explained, and deployed in real-world settings.”
The ad says“Build reliable analytical workflows using appropriate MLOps, and cloud-based practices, including version control, experiment tracking, automated testing, model monitoring, and scalable compute infrastructure”
The ad says“Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning”
The ad says“Strong programming capability in Python, including experience with scientific computing, machine learning frameworks, and data analysis libraries”
The ad says“Strong programming capability in Python, including experience with scientific computing, machine learning frameworks, and data analysis libraries”
The ad says“Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning”
The ad says“Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning”
The ad says“Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning”

Company Overview

Metrea delivers effects-as-a-service to national security partners across five domains and more than a dozen mission areas. These include airborne ISR, electronic warfare, secure communications, aerial refueling, special air missions, aerial firefighting, and advanced simulation. We own the whole stack: designing, building, and operating turnkey capabilities that give our partners decisive, asymmetric advantage against rapidly evolving threats.

Our operating model is built around three interlocking pillars. The Support Groups provide a global shared-service – spanning people, finance, platform, operations, legal, and engagement. This frees up our Core Groups, who develop and own mission capabilities end-to-end, to focus entirely on delivery. The Market Groups apply a regional lens, ensuring that our agile and adaptable capabilities remain aligned to the wicked problems that matter most to our partners across the Americas, EMEA, and Asia-Pacific.

At the heart of our model is a simple but powerful idea: be a true partner with skin in the game. Our partners need effects, not just equipment. By owning the full stack – from the lab to the field – we are able to drive a continuous cycle of innovation that keeps our partners ahead. It's a fast-moving, intellectually demanding environment where talented people are given real responsibility, work on problems that matter, and contribute to an enterprise that is growing quickly and deliberately.

Headquartered in Washington, DC, with facilities across the United States, the United Kingdom, as well as Continental Europe and Asia-Pacific.

Group Overview

The Digital and Synthetic Capability Unit (D&S) is committed to providing mission-driven information solutions that seamlessly bridge the digital and physical realms. Leveraging cutting-edge technologies and advanced platforms, we empower operational readiness and elevate situational awareness across diverse domains—including air, maritime, and space. 

Position Summary

In this role, you will apply machine learning, data science, and advanced analytical techniques to complex challenges across the electromagnetic environment. Working within Metrea’s Decision Science Laboratory (DESLAB) and automated Solution Engine, you will design, test, and deploy ML-enabled capabilities that go beyond traditional signal processing approaches. This includes exploring the potential of methods such as Transformers, self-supervised learning, probabilistic modelling and simulation-driven learning approaches for electromagnetic sensing and exploitation. You will be successful if you are comfortable moving between research, experimentation, and operational delivery, turning ambiguous Defence and Aerospace problems into robust technical solutions that can be tested, explained, and deployed in real-world settings.

What You'll Do

Translate operational requirements into technical solutions, working closely with cross-functional teams across decision science, electromagnetic simulation, waveform design, engineering, operations, hardware, and aerial systems
Apply machine learning, data science, and RF-aware analytical techniques to electromagnetic, problem sets, including spectrum classification, emitter detection, anomaly detection and signal characterisation
Explore and develop modern approaches for electromagnetic sensing and exploitation, including convolutional neural networks, transformers, autoencoders, graph-based methods or probabilistic approaches for uncertainty-aware decision-making
Design and conduct experiments to assess new algorithms and techniques
Develop proof-of-concept capabilities and support the deployment of selected approaches into operational environments
Liaise with forward-deployed teammates to understand real-world constraints, user needs, data limitations, environmental effects, and deployment considerations
Build reliable analytical workflows using appropriate MLOps, and cloud-based practices, including version control, experiment tracking, automated testing, model monitoring, and scalable compute infrastructure
Communicate complex technical concepts for no-technical users clearly through reports, demonstrations, briefings, and workshops
Mentor junior team members and help foster a collaborative, innovative, and technically rigorous environment, while staying current with emerging developments

What You Bring

A post-doctoral degree in a quantitative field such as Physics, Engineering, Mathematics, Computer Science, Statistics, or a related STEM discipline, or equivalent professional experience supported by a Master’s degree
Familiarity with modern approaches such as CNNs, Transformers, autoencoders, self-supervised learning, probabilistic modelling, or simulation-driven learning
Strong programming capability in Python, including experience with scientific computing, machine learning frameworks, and data analysis libraries
Experience applying data science, machine learning, or advanced analytics to electromagnetic or related operational problem sets
Ability to design rigorous experiments, evaluate model and algorithm performance, and translate findings into clear technical recommendations
Excellent communication skills, with the ability to explain complex ML, RF, statistical, and engineering concepts to technical and non-technical audiences
A collaborative mindset, strong technical curiosity, and the ability to work effectively in a fast-paced, mission-focused environment

Additional Eligibility Qualifications

Eligible to hold UK SC-level security clearance
Right to live and work in the UK

Benefits

Private Medical Insurance   
Subsided gym membership / plans through Wellhub   
Electric Car scheme   
Cycle to work scheme     
Free lunch on office days  
Enhanced Parental Leave  
30 days annual PTO plus b/h 
Bonus Scheme 
Personal development opportunities

Work Authorization / Security Clearance

The employee will have the legal right to work in the UK and will be able to produce right to work documentation. 

AAP/EEO Statement

Metrea is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or other characteristics protected by law. 

Position Type and Expected Hours of Work

This is a full-time non-exempt position with typical working hours of Monday through Friday, 9:00 a.m. to 6:00 p.m. Hours and work shifts may change in accordance with department and business needs.

Work Environment

This job operates in an office setting with hybrid working.

Travel

Occasional travel to other UK, Stockholm and US offices; predominantly in the UK.

Our Firmware

At Metrea, our single core value is Rooted in Humility, and our four cornerstone attributes are Entrepreneurial, Systematic, Discerning, and Over-Deliver. These form what we call our Teammate Firmware. Just like technical firmware connects software and hardware, our Firmware is the constant interface between our mission and our people. It defines how we show up, how we work together, and how we solve complex problems.

Our team Firmware creates a web-like, hyper-collaborative, dynamically hierarchical way of working that helps us adapt quickly, communicate openly, and distribute decision-making to where expertise actually lives. It enables groups to self-organize around hard problems, shift fluidly as priorities evolve, and operate with the trust, curiosity, and discipline required in a complex mission space. This foundation allows us to deliver elegant, effective solutions and uphold our purpose: protecting our precious inheritance.