If you’re working in data or ML and feel like you’re building pipelines or models that never quite make it into real‑world use, this is the kind of environment that changes that
- Data / Machine Learning Engineer (DV / eDV Cleared)
- Location: London (hybrid + high‑side work) Salary: £110,000 – £120,000 + bonus + DV incentives + benefits
We’re supporting a number of product‑led Defence and National Security organisations in London, building advanced data platforms and ML‑driven capabilities used in high‑impact, real‑world scenarios.
These teams tend to sit closer to the product and the end user, rather than operating as internal support functions.
What’s different about these roles?
You’re building things that actually get used.
These environments are typically:
- Product‑focused, with a strong engineering bar
- Set up for faster iteration than traditional programmes
- Focused on delivering usable outputs, not just research or theory
For engineers coming from large programmes or financial services, it’s often a shift towards more ownership and faster feedback loops.
What you’ll be doing
This will vary depending on the team, but typically includes:
- Building and maintaining scalable data pipelines
- Developing and deploying ML models into production environments
- Working closely with engineers, analysts, and end users to shape solutions
- Improving data availability, quality, and performance
- Contributing to the design of data platforms and ML systems
As with most roles in this space, some high‑side working and client interaction will be involved.
Typical tech environment
Most teams are working across:
- Python (core language for data and ML)
- Data processing frameworks (Spark, Pandas)
- Cloud platforms (AWS, sometimes Azure)
- ML frameworks (TensorFlow, PyTorch, Scikit‑learn)
- Data pipelines and orchestration tools
What they’re looking for
- Experience in Data Engineering, ML Engineering, or a hybrid role
- Strong Python skills and experience working with data at scale
- Experience deploying models or data products into production
- Comfortable working in fast‑moving, product‑focused teams
Active DV or eDV clearance is typically required.
Why it’s worth considering
- Work on genuinely impactful data and AI‑driven products
- Move closer to product and end‑user outcomes
- Strong engineering environments with high technical standards
- Base salaries between £110,000 – £120,000
- Additional DV bonuses, company bonus, and full benefits
If you’re looking to move into a more product‑driven environment where your work actually gets used, happy to talk through the different teams we’re supporting.
#J-18808-Ljbffr”, “datePosted”: “2026-05-01”, “hiringOrganization”: { “@type”: “Organization”, “name”: “Forwardrole”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__419928000__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=33” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “London” } } }If you’re working in data or ML and feel like you’re building pipelines or models that never quite make it into real‑world use, this is the kind of environment that changes that
- Data / Machine Learning Engineer (DV / eDV Cleared)
- Location: London (hybrid + high‑side work) Salary: £110,000 – £120,000 + bonus + DV incentives + benefits
We’re supporting a number of product‑led Defence and National Security organisations in London, building advanced data platforms and ML‑driven capabilities used in high‑impact, real‑world scenarios.
These teams tend to sit closer to the product and the end user, rather than operating as internal support functions.
What’s different about these roles?
You’re building things that actually get used.
These environments are typically:
- Product‑focused, with a strong engineering bar
- Set up for faster iteration than traditional programmes
- Focused on delivering usable outputs, not just research or theory
For engineers coming from large programmes or financial services, it’s often a shift towards more ownership and faster feedback loops.
What you’ll be doing
This will vary depending on the team, but typically includes:
- Building and maintaining scalable data pipelines
- Developing and deploying ML models into production environments
- Working closely with engineers, analysts, and end users to shape solutions
- Improving data availability, quality, and performance
- Contributing to the design of data platforms and ML systems
As with most roles in this space, some high‑side working and client interaction will be involved.
Typical tech environment
Most teams are working across:
- Python (core language for data and ML)
- Data processing frameworks (Spark, Pandas)
- Cloud platforms (AWS, sometimes Azure)
- ML frameworks (TensorFlow, PyTorch, Scikit‑learn)
- Data pipelines and orchestration tools
What they’re looking for
- Experience in Data Engineering, ML Engineering, or a hybrid role
- Strong Python skills and experience working with data at scale
- Experience deploying models or data products into production
- Comfortable working in fast‑moving, product‑focused teams
Active DV or eDV clearance is typically required.
Why it’s worth considering
- Work on genuinely impactful data and AI‑driven products
- Move closer to product and end‑user outcomes
- Strong engineering environments with high technical standards
- Base salaries between £110,000 – £120,000
- Additional DV bonuses, company bonus, and full benefits
If you’re looking to move into a more product‑driven environment where your work actually gets used, happy to talk through the different teams we’re supporting.
#J-18808-Ljbffr…