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- Tasks: Lead the development of machine learning models for a cutting-edge AI-driven platform.
- Company: Join a product-led MarTech company revolutionising digital content decisions.
- Benefits: Competitive salary, remote work, and opportunities for continuous learning.
- Why this job: Make a real impact by embedding AI into live workflows and improving marketing effectiveness.
- Qualifications: Strong experience in machine learning, advanced Python skills, and familiarity with ML libraries.
- Other info: Dynamic remote environment with a focus on collaboration and innovation.
The predicted salary is between 48000 - 72000 £ per year.
I am partnering with a product-led MarTech company building an AI-driven platform that helps teams make better decisions about digital content and performance. The platform applies machine learning to real-world data to analyse and improve how content performs at scale, moving decision-making away from guesswork and towards measurable insight. AI is a core part of the product and is already embedded in live, customer-facing workflows, running on a cloud-native stack with strong use of Google Cloud Platform (GCP).
What You’ll Be Doing
- Lead the development and deployment of machine learning models used in a live SaaS product
- Own models end-to-end from experimentation through production deployment, monitoring, and iteration
- Work closely with product, engineering, and non-technical stakeholders to embed AI into real workflows
- Improve the scalability, reliability, and performance of existing ML systems
- Review code and architecture, setting a high engineering standard
- Analyse data and run ad-hoc studies to generate actionable insights into marketing effectiveness
What They’re Looking For
- Strong experience as a Machine Learning Engineer / AI Engineer in a product-led environment
- Advanced Python skills and hands-on experience with PyTorch, TensorFlow, or similar ML libraries
- Experience deploying and maintaining ML models in production
- Solid software engineering fundamentals (algorithms, data structures, clean code)
- Comfortable working with Docker and containerised systems
- Experience collaborating cross-functionally and owning delivery, not just models
- A mindset focused on impact, curiosity, and continuous improvement
Machine Learning Engineer in Reading employer: TechByte Talent Ltd
Contact Detail:
TechByte Talent Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Reading
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself and make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s product. Be ready to discuss how your experience with Python, PyTorch, or TensorFlow can directly impact their AI-driven platform.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Machine Learning Engineer in Reading
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for machine learning and AI shine through. We want to see how your experience aligns with our mission of embedding AI into real workflows, so share specific examples of projects you've worked on that demonstrate your skills.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Machine Learning Engineer role. Highlight your advanced Python skills and experience with ML libraries like PyTorch or TensorFlow. We love seeing how your background fits with what we’re building at StudySmarter!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured documents that are easy to read. Use bullet points where necessary to make your achievements stand out, especially when discussing your experience in deploying and maintaining ML models.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining the StudySmarter team!
How to prepare for a job interview at TechByte Talent Ltd
✨Know Your ML Models Inside Out
Make sure you can discuss the machine learning models you've worked on in detail. Be prepared to explain your thought process from experimentation to deployment, and how you’ve iterated on them based on performance metrics.
✨Showcase Your Python Skills
Brush up on your advanced Python skills, especially with libraries like PyTorch and TensorFlow. Be ready to demonstrate your coding abilities, perhaps even through a live coding exercise or by discussing past projects where you used these tools.
✨Understand the Product and Its Users
Research the company’s AI-driven platform and think about how machine learning impacts their product. Be prepared to discuss how you would embed AI into workflows and improve marketing effectiveness based on data analysis.
✨Highlight Cross-Functional Collaboration
Prepare examples of how you've worked with non-technical stakeholders in the past. Emphasise your ability to communicate complex concepts clearly and how you’ve owned delivery beyond just the models themselves.
