At a Glance
- Tasks: Engineer cutting-edge machine learning solutions and optimise performance using Python.
- Company: Join Datatonic, a leading AI partner for Google Cloud, driving innovation.
- Benefits: Enjoy 25 days holiday, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and career advancement.
- Why this job: Shape the future of AI while working on impactful projects with top-tier clients.
- Qualifications: 1-3 years experience in machine learning and strong Python programming skills.
The predicted salary is between 60000 - 80000 £ per year.
At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world‑class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud. By partnering with us, clients future‑prove their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.
Your Mission: As a Machine Learning Engineer, you'll know how to engineer beautiful code in Python and take pride in what you produce. You'll be an advocate of high‑quality engineering and best‑practice in production software as well as rapid prototypes. Whilst the position is a hands‑on technical role, we'd be particularly interested to find candidates with a desire to lead projects and take an active role in leading client discussions. Your responsibilities will involve building trusted relationships with prospects, finding creative ways to use machine learning to solve problems, scoping projects, and overseeing the delivery of these engagements.
To be successful, you will need strong ML & Data Science fundamentals and will know the right tools and approach for each ML use case. You'll be comfortable with model optimisation and deployment tools and practices. Furthermore, you'll also need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI & Cloud.
What You’ll Do:
- Translating Requirements: Interpret vague requirements and develop models to solve real‑world problems.
- Data Science: Conduct ML experiments using programming languages with machine learning libraries.
- GenAI: Leverage generative AI to develop innovative solutions.
- Optimisation: Optimise machine learning solutions for performance and scalability.
- Custom Code: Implement tailored machine learning code to meet specific needs.
- Data Engineering: Ensure efficient data flow between databases and backend systems.
- MLOps: Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage.
- ML Architecture Design: Create machine learning architectures using Google Cloud tools and services.
- Engineering Software for Production: Build and deploy production‑grade software for machine learning and data‑driven solutions.
What You’ll Bring:
- Experience: 1‑3 years as a Machine Learning Engineer, preferably with a consulting background.
- Programming Skills: Proficiency in Python as a backend language, capable of delivering production‑ready code in well‑tested CI/CD pipelines.
- Cloud Expertise: Familiarity with cloud platforms such as Google Cloud, AWS, or Azure.
- Software Engineering: Hands‑on experience with foundational software engineering practices.
- Database Proficiency: Strong knowledge of SQL for querying and managing data.
- Scalability: Experience scaling computations using GPUs or distributed computing systems.
- ML Integration: Familiarity with exposing machine learning components through web services or wrappers (e.g., Flask in Python).
- Soft Skills: Strong communication and presentation skills to effectively convey technical concepts.
Bonus Points If You Have:
- Scale‑up experience.
- Cloud certifications (Google CDL, AWS Solution Architect, etc.).
What’s in It for You? We believe in empowering our team to thrive, with benefits including: Holiday: 25 days plus.
Machine Learning Engineer in London employer: Datatonic, Ltd.
At Datatonic, Ltd., we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. As a Senior Machine Learning Engineer, you will have access to cutting-edge technologies and opportunities for professional growth, all while working in a vibrant environment that values creativity and teamwork. Located in a dynamic tech hub, we offer competitive benefits and a chance to make a meaningful impact in the field of AI and data.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in London
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We think you need these skills to ace Machine Learning Engineer in London
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 Datatonic, Ltd., 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 Datatonic, Ltd.. 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 Datatonic, Ltd.
✨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!
✨Showcase Your Projects
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 Datatonic, Ltd.!
✨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.
