[Hiring] Senior ML Engineer @uSoftware

Role Description

We're looking for a Senior Machine Learning Engineer to help us unlock the next wave of value from our data. This is our first dedicated ML role - you'll be the person who establishes how machine learning is done here.

• You'll sit within the Data Engineering Squad and take ownership of ML use cases end-to-end - from identifying opportunities with stakeholders through to deploying and monitoring models in production.
• This is a hands-on senior individual contributor role.
• You won't manage people directly, but you will help shape our ML strategy alongside the Head of Data Engineering, Director of Analytics and Insight, and our incoming Chief Product Officer.
• While you'll be the primary ML specialist, you'll have strong support from Data Engineers, Analytics Engineers, and a leadership team that is actively investing in advanced analytics and AI.
• The company has an OKR to deliver multiple AI experiments each quarter - some will be selected and sponsored by the leadership team, but you'll also have significant freedom to drive your own agenda and identify opportunities independently.
• Our platform runs on Azure and Databricks. You'll work within that ecosystem to design, build and scale ML solutions that are reliable, observable and cost-effective.
• The current workload is primarily batch-oriented, with the business moving towards event-driven patterns across operational and analytics platforms - an early-stage journey you'll have the opportunity to help shape.

Qualifications

• Substantial experience in machine learning engineering, with a track record of deploying and maintaining models in a commercial product context - not just internal tooling.
• Demonstrated ability to work across the full ML lifecycle at a level where you're making design trade-offs, influencing system architecture and driving quality standards - not just building to a spec.
• Deep understanding of ML fundamentals - feature engineering, model selection, evaluation, hyperparameter tuning and the practical trade-offs involved.
• Experience designing and operating ML pipelines and infrastructure using IaC principles.
• Practical experience with MLflow or equivalent experiment tracking and model registry tooling.
• Strong proficiency in Python and SQL, and hands-on experience with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow.
• Excellent communication skills - you can translate technical concepts for non-technical stakeholders and build consensus across teams.

Requirements

• Experience with Databricks (ML Runtime, Feature Store, Unity Catalog, Model Serving).
• Familiarity with Azure ML services and AKS or container-based model serving architectures.
• Hands-on experience with Terraform, with a self-serve mindset towards provisioning and managing infrastructure.
• Exposure to LLMs, generative AI or agentic patterns - we see this as a growth area and would value someone who can help us navigate it.
• Awareness of data privacy, security and ML ethics considerations in a consumer-facing, data-rich environment.
• Experience in marketplace, e-commerce or classified advertising domains.

Benefits

• A genuine greenfield ML opportunity - you'll be the first dedicated ML hire and will shape the roadmap from day one.
• A modern data platform built on Databricks with strong Data Engineering foundations already in place.
• A business with rich, diverse data across dealers, vehicles, listings, consumer behaviour and leads.
• A leadership team actively investing in AI and advanced analytics, with a quarterly OKR cadence for experimentation.
• If you're motivated by turning data into products that create business value, and you want the autonomy to define how ML works here, we'd love to hear from you.