At a Glance
- Tasks: Build and deploy impactful AI solutions for diverse clients using machine learning.
- Company: Dynamic tech company focused on innovative AI solutions.
- Benefits: Unlimited annual leave, private healthcare, flexible working, and coaching support.
- Other info: Join a diverse team and thrive in a fast-paced, collaborative environment.
- Why this job: Make a real-world impact with cutting-edge machine learning technology.
- Qualifications: Experience in ML frameworks, strong Python skills, and cloud platform knowledge.
The predicted salary is between 60000 - 80000 £ per year.
Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients and cross‑functional teams, you'll ensure technical feasibility and timely delivery of high‑quality, production‑grade ML systems.
What you'll be doing:
- Building and deploying production‑grade ML software, tools, and infrastructure.
- Creating reusable, scalable solutions that accelerate the delivery of ML systems.
- Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.
- Leading technical scoping and architectural decisions to ensure project feasibility and impact.
- Defining and implementing Faculty’s standards for deploying machine learning at scale.
- Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.
Who we're looking for:
- You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit‑learn, TensorFlow, or PyTorch.
- You possess strong Python skills and solid experience in software engineering best practices.
- You bring hands‑on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.
- You have worked with container and orchestration tools such as Docker & Kubernetes to build and manage applications at scale.
- You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.
- You're an excellent communicator, able to guide technical teams and confidently advise non‑technical stakeholders.
- You thrive in a fast‑paced environment, and enjoy the autonomy to own scope, solve and deliver solutions.
Eligibility for UK Developed Vetting (DV) and willingness to work on site with clients may be required.
Benefits:
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working
We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Machine Learning Engineer employer: jobr.pro
As a Machine Learning Engineer at our company, you will be part of a dynamic and inclusive work culture that prioritises innovation and collaboration. With benefits like unlimited annual leave, private healthcare, and family-friendly flexibility, we empower our employees to thrive both personally and professionally. Located in a vibrant area, we offer unique opportunities for growth and development, ensuring that your contributions have a meaningful impact on diverse client projects.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Get Involved in Data Science Meetups
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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 jobr.pro.
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We think you need these skills to ace Machine Learning Engineer
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 jobr.pro, 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 jobr.pro. 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 jobr.pro
✨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!
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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 jobr.pro!
✨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.
