Machine Learning Engineer ofertas em United States

Adarga is the UK’s only sovereign Defence Tech company specialising in applied AI solutions across intelligence, operations and planning. In an era of information overload, Adarga delivers technology that enables our mission partners to act with speed, clarity and confidence. By unlocking the value of their data, we help our partners make better decisions that achieve mission-critical outcomes.

Our team is a hybrid of domain specialists and technologists. We believe this layering of experience is key to building cutting edge AI that is operationally relevant, solving real problems, to drive real outcomes.

This is a unique time to join Adarga. With our foundations set in NLP, computational linguistics and graph technology we now draw on the latest ideas in generative AI and knowledge representation, as we set our sights firmly on defining and building the next era of sovereign AI capability for mission partners across the Defence and National Security sectors.

To work at Adarga you have to care deeply about the mission. We exist to support those with the ultimate task: upholding the liberties and values that define our society. In today’s contested, multipolar world, this cannot be taken for granted.

We want people who are comfortable with uncertainty, who want to own decisions, who want to drive a vision. If that is you, get in touch!

If you don\'t match all the skills and qualifications but care about our mission then we\'d encourage you to back yourself and apply anyway. We all learn by doing

About the role:

This is a rare opportunity to design and build a first-of-its-kind adaptive intelligence platform designed for mission-critical environments. You’ll be working at the intersection of real-time data processing, multimodal ingestion, adaptive knowledge representation, and composable services, all built to operate across the most demanding deployment contexts (on-prem, cloud, and/or edge).

You’ll work side by side with defence and intelligence domain experts to drive rapid iteration cycles, ensuring what you build is grounded in real operational need. It’s a greenfield build where you’ll have full ownership of how core components come together, (e.g. ingestion pipelines, ontological reasoning layers, reusable capability services,) with the freedom to make smart, scalable technical decisions early. There’s no legacy stack and no hand-holding.

You’ll have the freedom to move fast, own critical decisions, and build a platform that could reshape how intelligence is used in modern operations.

Responsibilities:

• Architect and implement core infrastructure for a high-performance, adaptive intelligence platform.
• Build robust, scalable pipelines for ingesting and transforming multimodal data in real time.
• Design systems for knowledge representation and ontological reasoning that can adapt as information evolves.
• Develop composable services capable of deployment across cloud, edge, and on-prem environments.
• Collaborate with domain experts and end users to deeply understand operational constraints and mission needs.
• Lead technical design and decision-making while remaining hands-on in building and shipping code.
• Ensure systems are secure, reliable, and maintainable under demanding operational conditions.
• Drive a culture of pragmatic innovation, balancing rapid iteration with robust engineering standards.

Skills and Qualifications:

• A strong systems thinker and engineer with a track record of designing and delivering complex platforms.
• Proven experience building distributed systems, data pipelines, or infrastructure for mission- or safety-critical environments.
• Deep proficiency in at least one modern systems-level or backend programming language (e.g. Python, Rust, Go, or similar) with the ability to design, implement, and optimise performant, reliable software.
• Experience architecting systems that handle diverse data types—text, geospatial, sensor, temporal, etc.
• Familiarity with container orchestration and deployment across varied infrastructure contexts (e.g. Kubernetes, edge compute, air-gapped environments).
• Comfortable working autonomously and making early design decisions that will shape the future of the platform.
• A collaborative mindset—able to work closely with experts across AI, product, and defence domains.
• A growth-oriented engineer who thrives in ambiguity, iterates fast, and builds with care.

Interview Process

• Phone Interview – Remote (30 mins)
• Technical Interview – Remote/In person (1 h)
• Final Interview – Onsite (1 h)

Successful applicants may be required to undergo national security vetting upon appointment or during employment in this role. Applicants must meet the security requirements set out by UK Security Vetting (UKSV), and understand what is required in the associated UKSV: Vetting Guidance before they can be appointed.