Junior ML Engineer - Contract - SC Cleared

VIQU Limited; City Of London; Remote; GBP 32,000 - 48,000; Full time

Job summary

Morela is seeking a Junior Machine Learning Engineer to help stand up a brand new modelling and optimisation capability. This contract role (6 months, view to extend) is remote in the UK and requires active SC clearance, starting ASAP.

You will write production code, move models from notebooks to running reliably with real data, and build the pipelines and ingestion for physical, environmental and sensor data under supervision from senior engineers.

Qualifications

• Evidence you can build things: code you wrote that someone else has run.
• Fluent scientific Python, NumPy and SciPy.
• Good engineering habits: testing your own work and using Git in a team.
• Sufficient mathematical grounding from physics, maths, engineering or statistics backgrounds.
• Active SC clearance required.

Responsibilities

• Write production code and move models from prototype to production-ready.
• Build and test the pipelines and tooling the models run on.
• Handle ingestion and processing for physical, environmental and sensor data.
• Implement the optimisation that turns model outputs into decisions.
• Benchmark and validate your own work with independent checks.

Skills

Python

NumPy

SciPy

Git

Testing

Math background

Tools

Docker

Job description

MORELA

Junior Machine Learning Engineer

Contract | 6 months, view to extend | Remote (UK) | Active SC required | Start ASAP

The Role

A venture-backed UK AI business working in regulated and security-sensitive sectors is standing up a brand new modelling and optimisation capability, and needs a junior engineer to help build it.

You will spend your time writing code. The domain is physics-based performance modelling rather than LLM work, but the job is engineering: getting models out of notebooks and into something that runs reliably in production, alongside senior engineers who have done this before.

What You Will Be Doing

Writing production code and taking models from prototype to running reliably against real data.

Building and testing the pipelines and tooling the models run on.

Building the ingestion and processing for physical, environmental and sensor data.

Implementing the optimisation that turns model outputs into decisions.

Benchmarking and validating your own work, since the outputs get independently checked.

What You Will Need

Evidence you can build things. Code you have written yourself that someone else has run.

Fluent scientific Python, particularly NumPy and SciPy.

Proper engineering habits, testing your own work and using Git in a team.

Enough mathematical grounding for the domain, from a physics, maths, engineering or statistics background, or from modelling and simulation work picked up elsewhere.

Active SC clearance.

Useful but not essential: Docker, optimisation, time-series or signal processing, and any prior work in defence, government or another regulated environment.

Next Steps

Morela is proud to be supporting this search. Interviewing now.