Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join us as a Machine Learning Engineer, implementing best practices and operationalising models.
- Company: Work with a leading global IT and Digital transformation business on exciting government projects.
- Benefits: Enjoy hybrid working with 2 days remote and competitive pay of £550/day.
- Why this job: Be part of a dynamic team delivering impactful cloud solutions while enhancing your ML skills.
- Qualifications: Active SC Security Clearance and strong experience in Databricks, MLFlow, and MLOps required.
- Other info: Contract position for 2 months, starting ASAP in August 2025.
The predicted salary is between 45000 - 75000 £ per year.
Machine Learning Engineer (SC Cleared)
London (Hybrid)
2 Month Contract
£550/day (Inside IR35)
Machine Learning Engineer needed with active SC Security Clearance, plus strong Databricks, MLFlow and MLOps experience.
The ideal candidate will have a strong background in Machine Learning (ML) Engineering and in-depth expertise in operationalising models in Databricks, MLFlow and MLOps environments.
A chance to work with a leading global IT and Digital transformation business on the delivery of a complex cloud solution programme for a Government client.
Hybrid Working: 2 days/week remote (WFH), and 3 days/week working on-site in the London office. Start ASAP in August 2025.
Key experience + tasks will include:
- Implementing Databricks best practices in building and maintaining economic modelling (Machine Learning) pipelines.
- Working closely with Data Scientists and operationalizing model with auditing enabled, and ensuring the run can be reproduced.
- Ensuring models are modular, source controlled, and have agreed release numbering.
- Extracting hard-coded elements and parameterising them so model execution can be controlled via input parameters.
- Making sure model input parameters are version controlled + logged to the model execution runs for audit purposes.
- Ensuring model metrics are logged to model runs, model logging, monitoring + alerting to make sure any failure points are captured for the support team to investigate.
- Making sure re-runs of models involve running of multiple experiments + select the best model based on the accuracy and error rate of each experiment.
- Ensuring model is run in line with defined schedule, and that multiple models feeding oneanother take dependencies into account.
- Capturing data drift, concept drift, model performance degradation signals and ensuring model retrain.
- Defining / maintaining ML Frameworks (Python, R, Matlab templates), and looking for common reusable code that could be used by future models.
- Implementing CI/CD pipelines for ML models and automating deployment.
Machine Learning Engineer (SC Cleared) in City of London employer: Syntax Consultancy Limited
Contact Detail:
Syntax Consultancy Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (SC Cleared) in City of London
✨Tip Number 1
Make sure you brush up on your knowledge of Databricks, MLFlow, and MLOps. Familiarise yourself with best practices in these areas, as they are crucial for the role. Consider working on personal projects or contributing to open-source projects that utilise these technologies.
✨Tip Number 2
Since this position requires SC Security Clearance, ensure you have all necessary documentation ready. If you already hold this clearance, be prepared to discuss it during your conversations with us, as it can significantly strengthen your application.
✨Tip Number 3
Network with professionals in the Machine Learning field, especially those who have experience with government contracts. Attend relevant meetups or webinars to connect with others and gain insights into the specific requirements and expectations for this type of role.
✨Tip Number 4
Prepare to discuss your experience with CI/CD pipelines and automating deployment of ML models. Be ready to share specific examples of how you've implemented these processes in past projects, as this will demonstrate your hands-on expertise and problem-solving skills.
We think you need these skills to ace Machine Learning Engineer (SC Cleared) in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Databricks, MLFlow, and MLOps. Include specific projects where you've operationalised machine learning models, as this is crucial for the role.
Craft a Strong Cover Letter: In your cover letter, emphasise your active SC Security Clearance and how your skills align with the job requirements. Mention your experience in implementing best practices in ML pipelines and any relevant government projects.
Showcase Relevant Projects: If you have worked on similar projects, describe them in detail. Highlight your role, the technologies used, and the outcomes achieved. This will demonstrate your capability to handle the responsibilities of the position.
Proofread Your Application: Before submitting, carefully proofread your application for any errors or inconsistencies. A well-presented application reflects your attention to detail, which is essential for a Machine Learning Engineer.
How to prepare for a job interview at Syntax Consultancy Limited
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Databricks, MLFlow, and MLOps in detail. Highlight specific projects where you've implemented these technologies, focusing on the challenges you faced and how you overcame them.
✨Understand the Importance of Security Clearance
Since this role requires active SC Security Clearance, be ready to explain your understanding of its significance in the context of working with government clients. Discuss any previous experiences that demonstrate your ability to handle sensitive information responsibly.
✨Demonstrate Your Problem-Solving Skills
Prepare to discuss how you've operationalised machine learning models in past roles. Use examples to illustrate your approach to ensuring models are modular, source controlled, and how you manage version control for model parameters.
✨Emphasise Collaboration with Data Scientists
Highlight your experience working closely with data scientists. Discuss how you’ve collaborated to ensure models are reproducible and how you’ve contributed to the auditing process, as well as your role in capturing data drift and performance degradation.
