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For Companies At a Glance
- Tasks: Transform data science models into scalable machine learning solutions and build end-to-end ML pipelines.
- Company: Data-driven organisation focused on impactful machine learning solutions.
- Benefits: Competitive salary up to £90,000, flexible work, and collaborative culture.
- Why this job: Join a team that delivers real-world impact through innovative machine learning projects.
- Qualifications: 2+ years in machine learning, strong Python skills, and experience with ML frameworks.
- Other info: Dynamic environment with opportunities for professional growth and collaboration.
The predicted salary is between 54000 - 72000 £ 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 in London employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - Harnham in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow machine learning enthusiasts. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's GitHub repos or a personal website, let your work speak for itself and impress potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML interview questions and be ready to discuss your past projects in detail.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're serious about joining our team!
We think you need these skills to ace Senior Machine Learning Engineer - Harnham in London
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 client's goals. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Don’t forget to mention your experience with ML frameworks like Scikit-learn, TensorFlow, or PyTorch. We’re looking for someone who can hit the ground running, so highlight any relevant projects or deployments you've worked on.
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 don’t miss out on any important updates. Plus, we love seeing applications come in through our own channels!
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 skills made a difference.
✨Demonstrate Problem-Solving Abilities
Think of specific challenges you've faced in deploying ML models and how you overcame them. This could include discussing your approach to building end-to-end ML pipelines or implementing monitoring frameworks to ensure model reliability.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's current ML projects or their approach to operational improvements. This shows your genuine interest in the role and helps you understand how you can contribute to their goals.
