Forecasting and scoring
Demand and cash-flow forecasts, churn and propensity scores, and risk models, built with gradient boosting or time-series methods and tested against a naive baseline.
Hire Machine Learning developers · UK
Hire Machine Learning Developers in the UK
Machine learning engineers who start from the decision you want to improve, build the simplest model that beats today’s baseline, and keep it honest once it is live.
- Baseline first, then the model
- Explainable where decisions affect people
- You interview before anyone starts
Machine Learning expertise
Machine Learning expertise our developers bring.
From exploratory notebook to monitored production service — and an honest answer when a simple rule would beat a model.
Computer vision
Classification, object detection and segmentation for photos, scans and video frames, including the labelling workflow that produces the training data.
NLP and text classification
Routing, tagging and entity extraction for emails, complaints and contracts, with transformer models where they earn their cost and simpler ones where they do not.
Reproducible data pipelines
Feature pipelines from your databases and warehouse, with data validation and versioned datasets — no hand-edited CSVs in the loop.
MLOps
Experiment tracking, a model registry, CI for training code, deployment behind an API or as a batch job, and monitoring for drift and falling accuracy.
Explainability
SHAP and feature-importance reports, model cards and reason codes, so an underwriter, clinician or customer can see why a model decided what it did.
What they build
What Machine Learning developers can build for you.
The models UK organisations ask us for most — usually for a decision people make today with spreadsheets and experience.
Demand forecasting
Daily or weekly forecasts by product and site that feed purchasing and stock levels, with promotions, seasonality and bank holidays built in.
Risk and pricing models
Scoring and pricing models with reason codes, bias checks across customer groups and documentation your model risk and compliance teams can review.
Visual inspection
Cameras on the line that flag scratches, misprints or missing parts for an operator to confirm, trained on photos of your own defects.
Clinical imaging support
Models that flag findings on X-rays and scans for a clinician to confirm, with documentation to support your DCB0129 safety case and any MHRA medical device assessment.
Churn and lifetime value
Spot customers likely to cancel early enough to act, and estimate lifetime value so marketing spend goes where it pays back.
Anomaly detection
Flag unusual transactions, claims or meter readings for review, tuned to the number of alerts your team can realistically work through.
Technology stack
Technology stack.
The tools that usually sit around Machine Learning in the projects we join. We fit into your stack — this is where we are most at home.
Modelling
scikit-learnXGBoost and LightGBMPyTorchTensorFlow
Data engineering
Python, pandas and PolarsSQL and PostgreSQLdbtAirflow or Prefect
Vision and language
OpenCVHugging Face TransformersspaCyOCR pipelines
MLOps
MLflowDockerGitHub ActionsAWS SageMaker
Monitoring
Data drift checksEvidentlyPrediction loggingAlerting
Explainability
SHAPModel cardsReason codesFairness checks
Developer seniority
The right level for the work.
Every engagement is staffed with senior engineers. What changes is how much architecture and leadership the work needs around them.
Senior Machine Learning developer
Takes features from ticket to reviewed, tested, deployed code without hand-holding. The right choice for most roadmap work.
Lead engineer or architect
Sets the Machine Learning architecture, reviews the team's code and plans migrations, upgrades and scaling work.
A small blended pod
A Machine Learning developer with backend, QA or design support, coordinated by one delivery owner for larger scopes.
Engagement models
Ways to hire Machine Learning developers.
Pay by the hour for bursts of work, reserve a dedicated developer for your roadmap, or hand us the whole project.
Hourly Machine Learning developer
From £25 per hour
Backlog work, fixes, integrations, and flexible sprint support
- Weekly billing, daily written updates, code review, and no long-term lock-in.
Dedicated Machine Learning developer
From £3,600 per month
Ongoing delivery, product teams, and roadmap acceleration
- A named engineer embedded into your workflow with weekly demos and delivery planning.
Managed Machine Learning project
Fixed quote
MVPs, rebuilds, dashboards, SaaS platforms, and business-critical launches
- Discovery, architecture, development, QA, deployment, and post-launch support.
Prices are in GBP. Every estimate is confirmed in writing after a discovery call — the figures above are where engagements start, not a quote.
How hiring works
From brief to first commit.
The goal is not just to introduce a Machine Learning developer — it is to make the first week useful and the work visible from then on.
- 01
Discovery and fit check
We review your Machine Learning goals, current stack, deadlines, risks, and success metrics before suggesting an engagement model.
Role and success criteria agreed
- 02
Shortlist in 24 hours
You get a clear Machine Learning developer profile, relevant experience, availability, and estimated weekly capacity.
Developer profiles to review
- 03
Kick-off within days
We agree priorities, access, communication rhythm, delivery milestones, and code review expectations. Most engagements start within 5–7 working days of sign-off.
Access, rituals and first tickets
- 04
Ship with weekly demos
Every week you see working Machine Learning progress, blockers, next steps, and measurable delivery against the plan.
Visible progress every week
Why Techsleight
Why hire through Techsleight.
What you can hold us to — and what happens if something is not working.
You choose who joins
You see profiles and talk to the Machine Learning developer before anything starts, and nobody joins your team without your say-so.
Senior, production engineers
People who have shipped and supported real products — reviewed for code quality, testing habits and communication, not just a CV.
They work your way
Your repositories, tickets, stand-ups and review rules. Daily written updates and a weekly demo keep the work visible.
No lock-in
Hourly, dedicated or project-based, with short notice periods. Scale up for a launch and back down after it.
You own the code
Code, IP and documentation belong to you from day one. NDA before any detailed conversation, if you need one.
UK-focused delivery
UK business hours, GBP pricing and a contract with a UK company. Our engineers are based in the UK and India.
A whole team behind one hire
Backend, QA, DevOps and design colleagues are there when the Machine Learning work needs them — without you hiring for each role.
Relevant work
Machine Learning projects from our case studies.
Client work where Machine Learning was part of the stack. Each case study covers the brief, the approach and the result.
All case studiesFAQs
Questions we get asked.
Straight answers on scope, cost, timelines and how we work. If yours is not here, ask us directly.
Do we have enough data for machine learning?
Often more than you think, sometimes less than you hope. Forecasting needs enough consistent history to see several seasons; classification needs labelled examples of each outcome. We start with a short data audit and tell you whether a model, a rules engine or better data capture is the right next step.
Can you explain the decisions a model makes?
Yes. We use interpretable models where the stakes allow and SHAP-based reason codes where they do not, so each score comes with the factors behind it. The ICO’s guidance on explaining AI decisions and the UK GDPR rules on automated decision-making shape how we design review and challenge routes; your DPO and legal team sign off.
How do you keep a model accurate after launch?
We log inputs and predictions, compare them with outcomes as they arrive, and alert when incoming data drifts away from what the model was trained on. Retraining runs through the same tested pipeline, and a new version only replaces the old one after it performs better on held-out data.
Should we use machine learning or an LLM?
They solve different problems. For predicting a number or a category from structured data — sales, risk, churn — a trained model is usually cheaper, faster and easier to explain. LLMs are better at reading and writing unstructured text. Many good systems use both, and we will recommend whichever fits.
How much does it cost to hire a Machine Learning developer in the United Kingdom?
Machine Learning developer rates at Techsleight Labs start from £25/hour for flexible work and from £3,600/month for dedicated monthly capacity. Fixed-price Machine Learning projects are quoted after discovery, once scope, integrations, risks, and timeline are clear.
How quickly can a Machine Learning developer start?
Most Machine Learning engagements start within 5–7 working days of sign-off, and urgent work can sometimes start within 48–72 hours. For larger projects, we first confirm scope, architecture, milestones, and the right senior engineer fit before kickoff. We support UK teams with written updates, planned demos, and timezone-aware handover.
Can I hire one Machine Learning developer or a full team?
Yes. You can hire a single Machine Learning developer, add a small pod with QA and DevOps, or ask us to manage the complete project. We match the model to your current team, delivery pressure, and budget.
Are your Machine Learning developers senior?
Yes. Our hiring pages are built around senior production engineers, not junior bench resources. Every developer is reviewed for commercial project experience, communication quality, code quality, testing habits, and ability to work inside existing teams.
Do you work with existing Machine Learning codebases?
Yes. We often join existing Machine Learning projects to fix performance, unblock releases, add features, improve test coverage, or modernise architecture. We start with a codebase review so the first sprint is practical rather than theoretical.
What happens if the Machine Learning developer is not the right fit?
Tell us early. We will look at the cause with you — the brief, the onboarding or the match — and agree the next step together, such as more technical oversight, a different engagement model, or ending the engagement on the notice terms in your contract. The goal is a useful working relationship, not lock-in.
Hire developers
Ready to hire Machine Learning developers?
Tell us about the role — the codebase, the work and when you need someone. We will reply within one working day with next steps and suitable profiles.
What happens next
- 1A senior engineer reads your brief within one working day, and replies with questions or a first view.
- 2A 30-minute call to understand the goal, constraints and what good looks like — no sales script.
- 3A written proposal with scope, milestones, team and a GBP estimate you can take to your board.
Techsleight Labs is a trading name of Krapton IT Consultancy.
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