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# Lead Machine Learning Engineer - Pricing

- **Company:** Apex8
- **Location:** Tangmere, UK
- **Experience:** Expert
- **Salary:** £90,000.0 - £140,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Python (Programming Language), Machine Learning, Backtesting, Tensorflow, Standard Sql, Software Deployment, Unstructured Data, Supervised Learning, Feature Engineering, Pytorch, Model Validation, Scikit Learn, Xgboost, Machine Learning Operations
- **Published:** August 10, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=f0905b29531ef873

## About the Role

· Extensive commercial experience in Machine Learning, Data Science or a closely related field.

· Significant experience building and improving production ML models that directly influence commercial decisions.

· Proven ownership of ML projects from experimentation and development through to deployment, monitoring and continuous improvement.

· Excellent Python and SQL skills.

· Strong experience with technologies such as XGBoost, LightGBM, PyTorch, TensorFlow, scikit-learn or similar.

· Strong understanding of supervised learning, regression, ranking, forecasting, optimisation and feature engineering.

· Experience evaluating and improving existing ML models rather than only building greenfield solutions.

· Strong understanding of model evaluation, experimentation and backtesting.

· Experience deploying and operating ML solutions in live production environments.

· Comfortable working with large, noisy and rapidly changing real-world datasets.

· Strong commercial mindset with a focus on measurable financial outcomes.

· Comfortable working independently with significant autonomy and ownership.

Experience with computer vision, multimodal models or extracting commercially useful information from images would be highly advantageous.

Automotive experience is not essential. We are particularly interested in candidates who have built sophisticated pricing or decisioning systems within areas such as marketplaces, auctions, insurance, travel, trading, lending, betting or other pricing-intensive businesses., * Would you be happy with quarterly visits to PO202EU

 * Please detail your commercial experience in Machine Learning, Data Science or a closely related field.
 * We are particularly interested in candidates who have built sophisticated pricing or decisioning systems within areas such as marketplaces, auctions, insurance, travel, trading, lending, betting or other pricing-intensive businesses. Please confirm if this would apply to you and elaborate on your experience.

## Description

Every day we make thousands of pricing decisions. Every decision is a prediction, and every prediction affects conversion, margin and profitability.

We are looking for an exceptional Lead Machine Learning Engineer to take significant ownership of the Machine Learning behind how we value, buy and sell vehicles across our UK and US businesses.

We already have ML pricing models operating within the business and large volumes of proprietary historical data. Your role will be to understand what we have today, identify where it can be improved and develop increasingly sophisticated models and decisioning systems.

This is not a reporting, BI or traditional data role. We already have established Data and Engineering teams. This is a specialist, hands-on Machine Learning position for someone with extensive experience building and improving commercially important models and deploying them into production.

The problems are complex. Vehicles arrive with different faults, damage, mileage, condition and sometimes incomplete or imperfect information. Their values vary by geography, market conditions, buyer demand and disposal route.

We also want to make much better use of unstructured data. This includes using computer vision and modern AI techniques to understand vehicle condition and damage from customer-supplied photographs and incorporating this information directly into pricing decisions.

Beyond determining what a vehicle is worth, there are further optimisation problems around what we should pay for it, the probability of acquisition at different prices, its likely resale value and where or how it should ultimately be sold.

Your job will be to continually improve the intelligence behind these decisions.

Core Responsibilities

· Take ownership of improving and evolving our existing production ML pricing models.

· Design, build, validate and deploy new Machine Learning models for vehicle valuation, pricing and decisioning.

· Identify weaknesses and opportunities within our existing models and pricing architecture.

· Develop models that help determine the optimal price we should offer for individual vehicles.

· Predict vehicle resale values and auction outcomes across different disposal channels.

· Explore and implement computer vision models capable of identifying vehicle condition and damage from photographs.

· Combine structured vehicle information with image-derived and other unstructured data to improve pricing accuracy.

· Model complex factors including faults, damage, mileage, specification, geography, historic transactions, buyer demand, auction performance and changing market conditions.

· Optimise the relationship between offer price, customer conversion, acquisition probability, resale value, margin and overall profitability.

· Develop models appropriate to the different dynamics and datasets available within the UK and US markets.

· Engineer robust feature and model pipelines using large volumes of proprietary transactional and market data.

· Backtest and validate models before production deployment.

· Monitor model performance and drift and continually improve models as new data becomes available.

· Design experiments that allow us to measure the real commercial impact of model changes.

· Work closely with our Data and Engineering teams to integrate models into high-volume production systems.

· Research and apply emerging AI and Machine Learning techniques where they can materially improve our pricing and decision-making capability.


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