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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: Enjoy a competitive salary, remote work flexibility, and opportunities for professional growth.
- 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 continuous improvement.
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 Manchester 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 Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. We recommend including real-world applications and results to demonstrate your impact. This will make you stand out when applying through our website.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your past projects in detail. We suggest practicing common ML interview questions and coding challenges to boost your confidence.
✨Tip Number 4
Follow up after interviews! A quick thank-you email can go a long way. It shows your enthusiasm and keeps you fresh in their minds. Remember, we’re all about making connections that last!
We think you need these skills to ace Machine Learning Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Machine Learning Engineer, especially in product-led environments. We want to see your advanced Python skills and any hands-on work with ML libraries like PyTorch or TensorFlow.
Showcase Your Projects: Include specific examples of machine learning models you've developed and deployed. We love seeing end-to-end ownership, so share how you took models from experimentation to production and what impact they had.
Highlight Collaboration Skills: Since we work closely with product and engineering teams, it’s important to demonstrate your ability to collaborate cross-functionally. Share experiences where you’ve worked with non-technical stakeholders to embed AI into workflows.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
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 Coding Skills
Brush up on your Python skills and be ready to demonstrate your proficiency with libraries like PyTorch or TensorFlow. You might be asked to solve coding problems or review code during the interview, so practice clean coding and algorithms.
✨Understand the Product and Its Users
Research the company’s AI-driven platform and think about how machine learning impacts their product. Be ready 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 building models.
