Production ML Engineer - Build Scalable Pipelines & MLOps in London

Production ML Engineer - Build Scalable Pipelines & MLOps in London

London Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
Data Science Festival

At a Glance

  • Tasks: Design and build robust data pipelines for scalable ML systems.
  • Company: Join Data Science Festival, a leader in AI and data innovation.
  • Benefits: Enjoy competitive salary, generous holidays, and career progression.
  • Other info: Collaborative hybrid work environment with growth opportunities.
  • Why this job: Make a real impact on how millions engage with products.
  • Qualifications: Experience in machine learning and data pipeline development.

The predicted salary is between 70000 - 90000 £ per year.

Data Science Festival is seeking a Machine Learning Engineer to design and build robust data pipelines while transforming ML prototypes into production-ready systems. This role directly influences how millions engage with products, ensuring data and AI strategies scale effectively. You will work closely with analysts and data engineers in a hybrid setting, focusing on reliable, scalable models.

Benefits include competitive salary, generous holidays, and career progression opportunities.

Production ML Engineer - Build Scalable Pipelines & MLOps in London employer: Data Science Festival

Data Science Festival is an exceptional employer that fosters a collaborative and innovative work culture, where your contributions as a Production ML Engineer will directly impact millions of users. With a focus on employee growth, we offer competitive salaries, generous holiday allowances, and ample opportunities for career progression in a hybrid working environment that values both flexibility and teamwork.

Data Science Festival

Contact Details:

Data Science Festival Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Production ML Engineer - Build Scalable Pipelines & MLOps in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Data Science Festival!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Production ML Engineer - Build Scalable Pipelines & MLOps at Data Science Festival.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Data Science Festival.

Apply Directly through Our Website

When you find a suitable opening like Production ML Engineer - Build Scalable Pipelines & MLOps at Data Science Festival, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Production ML Engineer - Build Scalable Pipelines & MLOps in London

Machine Learning
Data Pipeline Design
MLOps
Production Systems Development
Collaboration with Analysts
Collaboration with Data Engineers
Scalability

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Data Science Festival, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Data Science Festival. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Data Science Festival

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Data Science Festival!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.