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- Tasks: Design and build data pipelines, transform ML prototypes into production-ready systems.
- Company: Join a leading tech firm with a focus on data and AI innovation.
- Benefits: Competitive salary, hybrid work model, generous holiday allowance, wellness facilities.
- Why this job: Make a real impact by influencing how millions engage with products daily.
- Qualifications: Degree in relevant field and experience in data or ML engineering.
- Other info: Clear career progression and opportunities to work with cutting-edge technology.
The predicted salary is between 44000 - 66000 £ per year.
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.
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!
Machine Learning Engineer in City of London employer: Data Science Festival
Contact Detail:
Data Science Festival Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning Engineers on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and ML models. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and SQL skills. Practice coding challenges and be ready to discuss your experience with cloud platforms and MLOps best practices. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates who are eager to join our team.
We think you need these skills to ace Machine Learning Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing your projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Since this role involves hands-on work with Python, SQL, and cloud platforms, make sure to mention any relevant tools or technologies you’ve used. We’re keen to see your technical prowess in action!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Data Science Festival
✨Know Your Tech Stack
Make sure you’re well-versed in the tools mentioned in the job description, like Python, SQL, and cloud platforms such as GCP or Azure. Brush up on your experience with MLflow, Vertex AI, or Azure ML, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built data pipelines or deployed ML models. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand MLOps Best Practices
Familiarise yourself with MLOps principles, including CI/CD, experiment tracking, and model governance. Be prepared to discuss how you’ve implemented these practices in past roles or how you would approach them in this new position.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy, team dynamics, and the technologies they use. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
