At a Glance
- Tasks: Build and scale infrastructure for cutting-edge AI systems and optimise ML workflows.
- Company: Fast-growing AI company with over £100m raised, focused on innovative solutions.
- Benefits: Competitive salary up to £150k, hybrid work model, and strong career growth.
- Other info: Collaborate directly with scientists and shape the future of AI technology.
- Why this job: Join a small, senior team and make a real impact in the AI landscape.
- Qualifications: Experience in ML systems engineering and strong Python skills required.
The predicted salary is between 80000 - 98000 £ per year.
We’re working with a fast-growing AI company building production systems for training and deploying cutting-edge multimodal models across video, embeddings, and large-scale metadata.
You’ll join a small, highly technical team owning the ML infrastructure and systems layer end-to-end — from large-scale data ingestion and training pipelines through to high-performance production inference.
What you’ll be doing:
- Building and scaling infrastructure for massive multimodal datasets
- Improving distributed ML training systems using PyTorch and Ray
- Developing tooling for experimentation, evaluation, and dataset analysis
- Owning model lifecycle workflows across training, deployment, and rollout
- Optimising GPU inference systems for performance, latency, and reliability
What they’re looking for:
- Strong background in ML systems engineering or production ML infrastructure
- Experience deploying ML models into real-world production environments
- Strong Python skills plus experience with a systems language (C++ / Java etc.)
- Experience working with distributed systems and large-scale datasets
- Engineers who enjoy solving practical problems end-to-end rather than purely research work
Tech:
- Python, PyTorch, Ray
- Distributed systems & GPU infrastructure
- Large-scale data platforms
- ML serving & inference systems
Why it’s interesting:
- Real-world AI systems operating at significant scale
- High ownership within a small, senior engineering team
- Direct collaboration with applied scientists and research teams
- Strong commercial traction and significant backing
- Opportunity to help shape the next stage of platform growth
Senior Machine Learning Engineer in Slough employer: Atarus
Join a dynamic and well-funded AI company in London, where you'll be part of a small, highly skilled team dedicated to building cutting-edge machine learning infrastructure. With a strong focus on employee growth and collaboration, this role offers the chance to work on real-world AI systems at scale, while enjoying a hybrid work environment and competitive salary. The company fosters a culture of innovation and ownership, providing unique opportunities for professional development and direct impact on the platform's evolution.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning 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 Atarus!
✨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 Senior Machine Learning Engineer at Atarus.
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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 Atarus.
✨Apply Directly through Our Website
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We think you need these skills to ace Senior Machine Learning 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 Atarus, 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 Atarus. 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 Atarus
✨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 Atarus!
✨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.
