Machine Learning Engineer
Salary: £60,00 - £65,000
Location: London - Hybrid - 2 days
We are currently looking for a Machine Learning Engineer to join our client's data team. This is a hands-on role where you'll design and build robust data pipelines, transform ML prototypes into production-ready systems, and champion MLOps best practices across the business. As a Machine Learning Engineer, you'll play a crucial role in ensuring our clients' data and AI strategy scales effectively, directly influencing the way millions of people engage with their products every day.
The Opportunity
This is a unique chance to combine data engineering with machine learning in a high-impact environment. You'll work closely with analysts, data engineers and stakeholders, ensuring models are reliable, scalable, and production-ready. Unlike many roles in the tech sector, this Machine Learning Engineer role gives you the visibility of seeing your work applied at scale, powering decision-making and user experiences for a vast audience.
Your day-to-day will include:
Building and maintaining end-to-end data pipelines and feature engineering workflows.
Deploying and monitoring ML models in production using tools such as MLflow, Vertex AI, or Azure ML.
Driving best practices in MLOps, including CI/CD, experiment tracking, and model governance.
Supporting the data warehouse and ensuring data quality, governance, and accessibility.
Collaborating with cross-functional teams to deliver trusted datasets and insights.
What's in it for you?
Competitive salary with annual reviews.
Hybrid working model offering flexibility.
Generous holiday allowance that increases with service.
Onsite wellness facilities, subsidised meals, and gym access.
Access to wellbeing support services and employee assistance programmes.
Clear career progression and opportunities to work with cutting-edge tech.
Skills and Experience
Degree in Computer Science, Engineering, Mathematics, or a related field.
Proven experience in data or ML engineering.
Strong knowledge of Python and SQL.
Hands-on experience with cloud platforms (GCP or Azure) and Databricks.
Familiarity with deploying ML workflows using MLflow, Vertex AI, or Azure ML.
Nice-to-have:
Experience with Spark, CI/CD pipelines, and orchestration tools.
Knowledge of Elasticsearch or digital/web analytics platforms.
Understanding of the full machine learning lifecycle, from experimentation to evaluation.
If you would like to be considered for the Machine Learning Engineer role and feel you'd be an ideal fit for our team, please click the Apply button to submit your CV. We look forward to hearing from you
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