At a Glance
- Tasks: Build and deploy machine learning models using PyTorch for real-world applications.
- Company: Join System1, a leading company in innovative advertising solutions.
- Benefits: Enjoy hybrid work, ongoing learning opportunities, and a supportive team environment.
- Other info: Collaborative culture with a focus on professional growth and development.
- Why this job: Make a real impact by working with cutting-edge technology on exciting projects.
- Qualifications: Experience in machine learning, deep learning, and model deployment.
The predicted salary is between 80000 - 98000 £ per year.
System1 in the United Kingdom is seeking a pragmatic Machine Learning Engineer to join a talented product team.
You will build, train and deploy models powering our Ad, Brand and Innovation products, working with text, image and video data to drive real customer impact.
You’ll apply classic ML, deep learning and LLMs, ensuring reproducible experiments, clear documentation, and smooth handoff to engineering for deployment.
Hybrid work and ongoing learning are encouraged.
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ML Engineer Real-World Predictive Models in PyTorch employer: System1
At System1, we pride ourselves on being an excellent employer by fostering a collaborative work culture that empowers our employees to innovate and excel in their roles. Located in the vibrant Greater London area, we offer competitive salaries, comprehensive health insurance, and education reimbursement, ensuring our team members have the support they need for personal and professional growth. Join us to be part of a forward-thinking company that values creativity and meaningful contributions in the realm of AI-powered design.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer Real-World Predictive Models in PyTorch
✨Get Involved in Data Science Meetups
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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 System1.
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We think you need these skills to ace ML Engineer Real-World Predictive Models in PyTorch
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 System1, 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 System1. 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 System1
✨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 System1!
✨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.
