At a Glance
- Tasks: Design, build, and deploy cutting-edge ML systems from data prep to inference.
- Company: Join a fast-moving start-up with exciting equity options.
- Benefits: Fully remote role with competitive salary and equity opportunities.
- Other info: Enjoy end-to-end ownership in a dynamic and innovative environment.
- Why this job: Make an impact by turning research into reliable production solutions.
- Qualifications: Strong Python skills and experience with PyTorch or JAX required.
The predicted salary is between 80000 - 100000 £ per year.
Mc Gregor Boyall is seeking a Senior Machine Learning Engineer for a fully remote, Europe-wide role.
You will design, build and deploy production ML systems, owning the full lifecycle from data prep to inference, turning research into reliable production solutions.
The role covers end-to-end ownership in a fast-moving start-up environment with equity options.
The position requires strong Python software engineering, experience with Py Torch and/or JAX, and a track record of deploying modern ML #J-18808-Ljbffr
Remote Principal ML Engineer - Production Systems, Equity in London employer: McGregor Boyall
Join a prestigious financial institution in Dublin as a Remote Python Risk Developer, where you'll be at the forefront of developing innovative risk management solutions for Emerging Markets. Enjoy a competitive contract rate and the flexibility of hybrid working, all while collaborating with top-tier professionals in a dynamic environment that fosters professional growth and exposure to high-profile projects. This role not only offers the chance to work with cutting-edge technology but also encourages continuous learning in advanced risk management practices.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Principal ML Engineer - Production Systems, Equity in London
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We think you need these skills to ace Remote Principal ML Engineer - Production Systems, Equity in London
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 McGregor Boyall, 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 McGregor Boyall. 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 McGregor Boyall
✨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!
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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 McGregor Boyall!
✨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.
