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- Tasks: Transform data science models into scalable machine learning solutions and build end-to-end ML pipelines.
- Company: A data-driven organisation focused on impactful machine learning solutions.
- Benefits: Competitive salary up to £90,000, flexible work, and opportunities for professional growth.
- Why this job: Make a real impact by deploying innovative ML solutions across various industries.
- Qualifications: 2+ years in machine learning, strong Python skills, and experience with ML frameworks.
- Other info: Collaborative environment with excellent career advancement opportunities.
The predicted salary is between 54000 - 90000 £ per year.
About The Role
Our client is a data-driven organisation focused on delivering measurable operational and financial improvements across a range of industries. They combine deep technical expertise with real-world delivery to design, build and deploy machine learning solutions that create tangible business impact.
Machine Learning Engineer
London – 3 days a week in office | Up to £90,000
Responsibilities
- Translating data science models into scalable, production-ready machine learning solutions.
- Designing and building end-to-end ML pipelines, from data ingestion to deployment and monitoring.
- Collaborating with data engineers on data architecture, pipelines and feature stores.
- Working closely with data scientists to productionise models and improve performance.
- Deploying, monitoring and maintaining machine learning models in live environments.
- Implementing testing, validation and monitoring frameworks to ensure model reliability and impact.
Your work will focus on delivering high-value ML solutions, including:
- Productionising optimisation and predictive models at scale.
- Building systems to anticipate and prevent operational downtime.
- Deploying churn and customer behaviour models into live decision-making systems.
- Enabling next-best-action and recommendation engines for commercial teams.
- Supporting geospatial and advanced analytical models with robust ML infrastructure.
What We’re Looking For
- 2+ years’ experience building and deploying production machine learning systems.
- A strong academic background (Bachelor’s degree 2:1 or above in a quantitative subject).
- Strong Python skills and experience with ML frameworks (e.g. Scikit-learn, TensorFlow, PyTorch).
- Experience with model deployment, monitoring and ML pipelines (e.g. CI/CD, MLOps concepts).
- A collaborative mindset with strong communication skills and experience working in cross-functional teams.
If this role looks of interest, apply below.
Senior Machine Learning Engineer - Harnham employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - Harnham
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. 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 GitHub repos or a personal website, having tangible examples of your work can really set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common ML interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨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’s a great way to get noticed by our hiring team.
We think you need these skills to ace Senior Machine Learning Engineer - Harnham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning systems and Python skills. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Since this role requires strong technical expertise, make sure to mention specific ML frameworks you’ve worked with, like Scikit-learn or TensorFlow. We’re keen to know how you’ve applied these in real-world scenarios.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Jobster
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and frameworks like Scikit-learn, TensorFlow, and PyTorch. Be ready to discuss your past projects and how you've translated data science models into production-ready solutions.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data engineers and scientists, be prepared to share examples of how you've successfully collaborated in cross-functional teams. Highlight any experiences where your communication made a difference in project outcomes.
✨Demonstrate Problem-Solving Abilities
Think of specific challenges you've faced in deploying or monitoring ML models and how you overcame them. This will show your potential employer that you can handle real-world problems and deliver high-value ML solutions.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's approach to machine learning and their current projects. This not only shows your interest but also gives you a chance to assess if the company aligns with your career goals.
