At a Glance
- Tasks: Build and own the MLOps and data engineering strategy from scratch.
- Company: Exciting AI startup tackling major challenges in the mining industry.
- Benefits: Competitive salary, meaningful equity, and the chance to shape the ML platform.
- Other info: Work closely with experienced founders and engineers on challenging technical problems.
- Why this job: Join a dynamic team and make a real impact in a fast-paced environment.
- Qualifications: Strong Python skills and experience with MLOps infrastructure required.
The predicted salary is between 70000 - 100000 £ per year.
A venture-backed AI startup that's using machine learning to solve one of the biggest challenges in the mining industry is looking for a Founding MLOps & Data Engineer to build the infrastructure that takes cutting-edge ML into production.
What will I be doing?
- Own the company's MLOps and data engineering strategy from the ground up.
- Build scalable data pipelines and production ML infrastructure.
- Develop reproducible, versioned and auditable machine learning workflows.
- Work closely with ML researchers to productionise new models.
- Collaborate with product engineers to integrate ML into customer-facing applications.
- Shape the architecture of the ML platform as the company grows, with plenty of autonomy to influence technical decisions.
What we're looking for:
- Strong Python engineering skills with experience building production data pipelines.
- Commercial experience owning MLOps infrastructure and deploying machine learning models.
- Experience working with cloud platforms (Azure, AWS or GCP).
- A self-starter who enjoys working in fast-paced startup environments with lots of ownership.
- Someone who can work through ambiguity, prioritise effectively and solve problems independently.
- Geospatial ML or scientific computing experience would be a plus.
- Experience working in an early-stage or founding engineering team.
What's in it for you?
- Salary between £70,000 - £100,000 depending on experience.
- Meaningful equity in a well-funded, early-stage startup.
- The opportunity to build and own the company's ML platform from day one.
- Work alongside experienced founders and engineers tackling genuinely difficult technical problems.
Apply now for immediate consideration!
Founding MLOps & Data Engineer in Slough employer: Understanding Recruitment
Join a pioneering AI startup in London, where you'll have the unique opportunity to shape the MLOps and data engineering landscape from the ground up. With a strong focus on innovation, our collaborative work culture fosters autonomy and encourages personal growth, while offering competitive salaries and meaningful equity. Be part of a dynamic team dedicated to solving significant challenges in the mining industry, all within a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Founding MLOps & Data Engineer in Slough
✨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 Understanding Recruitment!
✨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 Founding MLOps & Data Engineer at Understanding Recruitment.
✨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 Understanding Recruitment.
✨Apply Directly through Our Website
When you find a suitable opening like Founding MLOps & Data Engineer at Understanding Recruitment, 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 Founding MLOps & Data Engineer in Slough
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 Understanding Recruitment, 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 Understanding Recruitment. 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 Understanding Recruitment
✨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 Understanding Recruitment!
✨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.
