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, private health insurance, gym discounts, and a hybrid work model.
- Other info: Access to learning platforms and excellent career growth opportunities.
- Why this job: Shape the future of AI while working with passionate experts in a dynamic environment.
- Qualifications: 1-3 years experience in machine learning, strong Python skills, and cloud familiarity.
The predicted salary is between 30000 - 42000 £ per year.
Shape the Future of AI & Data with Us. 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-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.
Your Mission: As a Machine Learning Engineer, you will engineer beautiful code in Python and take pride in what you produce. You will be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes. This is a hands-on technical role, and we are particularly interested in 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 will be comfortable with model optimisation and deployment tools and practices. Furthermore, you will 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 bank holidays.
- Health Perks: Private health insurance (Vitality Health) and Smart Health Services.
- Fitness & Wellbeing: 50% gym membership discounts (Nuffield Health, Virgin Active, Pure Gym).
- Hybrid Model: A WFH allowance to keep you comfortable.
- Learning & Growth: Access to platforms like Udemy to fuel your curiosity.
- Pension: Auto-enrolment after probation period. 3% employer contributions raising 1% per year of service to a max of 10%.
- Life Insurance: 3 x your base salary.
- Income Protection: up to 75% of base salary, up to 2 years.
- Cycle to Work Scheme.
- Tech Scheme.
Why Datatonic? Join us to work alongside AI enthusiasts and data experts who are shaping tomorrow. At Datatonic, innovation isn’t just encouraged - it’s embedded in everything we do. If you’re ready to inspire change and deliver value at the forefront of data and AI, we’d love to hear from you! Are you ready to make an impact? Apply now and take your career to the next level.
Machine Learning Engineer in London employer: Datatonic
At Datatonic, we pride ourselves on being a leading employer in the AI and data sector, offering a vibrant work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through access to learning platforms like Udemy, alongside competitive benefits such as private health insurance, generous holiday allowances, and a hybrid working model. Join us in London, where you will be part of a dynamic team dedicated to pushing the boundaries of technology and making a meaningful impact in the world of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer 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 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 a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common ML scenarios and coding challenges. Brush up on your Python skills and be ready to discuss your thought process. Remember, it’s not just about getting the right answer but how you approach the problem!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at Datatonic. Tailor your application to highlight how your skills align with our mission in AI and data.
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Machine Learning Engineer role. Highlight your experience with Python, ML fundamentals, and any relevant projects that showcase your skills. We want to see how you fit into our vision!
Showcase Your Projects:Include links to your GitHub or any other portfolio where we can see your code in action. Demonstrating your hands-on experience with machine learning models and production-ready software will definitely catch our eye!
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your experiences and achievements. We appreciate a well-structured application that gets straight to the point without unnecessary fluff.
Apply Through Our Website:Don’t forget to submit your application through our official website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Datatonic
✨Know Your Code
Make sure you’re comfortable discussing your Python code and any machine learning models you've built. Be ready to explain your thought process, the challenges you faced, and how you optimised your solutions. This shows your technical prowess and problem-solving skills.
✨Understand the Business
Research Datatonic and understand their approach to AI and data solutions. Be prepared to discuss how your skills can help them meet their clients' needs. This will demonstrate your interest in the company and your ability to align your work with business goals.
✨Showcase Your Communication Skills
Since this role involves client discussions, practice explaining complex technical concepts in simple terms. Use examples from your past experiences where you successfully communicated with non-technical stakeholders to highlight your consulting abilities.
✨Prepare for Scenario Questions
Expect questions that ask you to solve hypothetical problems or optimise existing models. Think through potential scenarios related to machine learning and be ready to discuss your approach to tackling these challenges, showcasing your analytical thinking and creativity.
