Senior Machine Learning Engineer
Role details
Job location
Tech stack
Job description
We are looking for a Senior Machine Learning Engineer to bring intelligent automation and predictive capability to the heart of the UK property market. Alto sits at a unique intersection: we process an enormous volume of real transaction data, and we're only beginning to unlock what that means for the products our customers rely on every day. This is a role for someone who wants to build ML systems that genuinely change how people buy and sell homes - not maintain models that gather dust.
What You'll Do
- Design, build, and deploy end-to-end machine learning pipelines - from data ingestion and feature engineering through to model serving and monitoring in production.
- Own the full lifecycle of ML models: evaluate, iterate, and retire them with the same rigour you bring to building them.
- Collaborate closely with product and engineering teams to frame business problems as machine learning problems, and translate model outputs into product features users actually understand.
- Establish and maintain standards for ML reproducibility, experiment tracking, and model versioning across the Data team.
- Identify opportunities to apply ML across Alto's product suite - surfacing ideas proactively, not waiting to be briefed.
- Work with large, complex datasets drawn from live UK property transactions, ensuring data quality and feature reliability upstream of every model.
- Contribute to a culture of engineering excellence through code reviews, documentation, and knowledge-sharing with data engineers and analysts., This role gives you genuine ownership of ML capability at a company that processes more housing transactions than anyone else in the UK - the data advantage is real and largely untapped. You will have the scope to define how machine learning is built and deployed at Alto, not slot into a pre-defined process. It's an exciting moment to join: we're investing seriously in our Data function, and this hire will shape its direction.
Requirements
- Proven experience building and shipping machine learning models into production environments - not just notebooks and prototypes.
- Strong Python skills and hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow.
- Solid understanding of MLOps principles: model serving, monitoring, drift detection, and retraining pipelines.
- Experience working with cloud infrastructure - AWS preferred - and comfort deploying models in containerised or serverless environments.
- A rigorous, statistically grounded approach to model evaluation - you know when a model is good enough and when it isn't.
- The ability to communicate model behaviour and limitations clearly to non-technical stakeholders.
- Familiarity with data pipeline tooling (e.g. Airflow, dbt, Spark) and an understanding of how ML fits within a broader data platform.
There's always room to grow and learn with our roles - please don't be put off if you don't have all of these. It's more important that you're passionate about improving the home moving and owning experience for everyone.
Our Technology Stack
- Backend: TypeScript, Node.js, C#, .NET
- Infrastructure: AWS (ECS, Lambda, SQS, DynamoDB), Terraform
- Architecture: Microservices, Event-driven architecture
- Data & ML: Python, AWS SageMaker, S3, Redshift
Benefits & conditions
Pulled from the full job description
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Referral programme
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Annual leave
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Company pension
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Paid volunteer time
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On-site gym
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Private medical insurance
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Cycle to work scheme, * 25 days annual leave + extra days for years of service
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Day off for volunteering & Digital detox day
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Festive Closure - business closed for period between Christmas and New Year
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Cycle to work and electric car schemes
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Free Calm App membership
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Enhanced Parental leave
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Fertility Treatment Financial Support
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Group Income Protection and private medical insurance
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Gym on-site in London
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7.5% pension contribution by the company
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Discretionary annual bonus up to 10% of base salary
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Talent referral bonus up to £5K