Houseful
Senior Machine Learning Engineer

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Senior Machine Learning Engineer
Alto Software Group
Alto Software Group is a B2B SaaS company that powers more than half of all UK housing transactions each year. We create software solutions that connect businesses and consumers, delivering a one-stop shop for estate agents and home builders. Our goal is to drive efficiency, speed up transactions, reduce risk, and improve the end-customer experience. While we're not a start-up, we have a start-up mindset and want our people to operate with this mindset so that we can achieve our ambitions.
The Role
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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What You Need to Be Successful
- 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.


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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
Why Join Alto?
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.
- 25 days annual leave + extra days for years of service
- Day off for volunteering & Digital detox day
- Festive Closure - business closed for period between Christmas and New Year
- Cycle to work and electric car schemes
- Free Calm App membership
- Enhanced Parental leave
- Fertility Treatment Financial Support
- Group Income Protection and private medical insurance
- Gym on-site in London
- 7.5% pension contribution by the company
- Discretionary annual bonus up to 10% of base salary
- Talent referral bonus up to £5K
We want to make Alto more welcoming, fair and representative every day. We’ll consider everyone who applies for this role in the same way, regardless of your ethnicity, colour, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, neurodiversity status, family or parental status, or how long you’ve spent unemployed.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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