At a Glance
- Tasks: Build and scale cutting-edge machine learning solutions for real AI workflows.
- Company: Join Encord, a leading AI data platform trusted by top companies.
- Benefits: Competitive salary, equity, 25 days leave, and a vibrant office culture.
- Other info: Enjoy monthly socials, team offsites, and a focus on professional growth.
- Why this job: Make a direct impact in AI while collaborating with innovative teams.
- Qualifications: 3+ years in machine learning, strong Python skills, and collaborative mindset.
The predicted salary is between 70000 - 90000 £ per year.
Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more.
We are looking for an experienced Machine Learning Engineer to join our team and help us build and scale cutting‑edge machine learning and computer vision solutions that power real AI workflows. You'll work hands‑on across the full ML lifecycle — from experimenting with the latest models and techniques to integrating them into a production platform used by hundreds of AI teams worldwide.
This is a highly collaborative role where you'll partner closely with our product engineering and human data teams to turn complex algorithmic ideas into reliable, scalable features that customers love. Our work is at the cutting edge of computer vision and deep learning, which also includes working on solving unsolved problems within those fields.
If you're someone who thrives at the intersection of strong ML fundamentals and practical engineering, and wants to see their work make a direct impact at scale — this is the role for you.
What you'll do:
- Experiment with and adapt the latest ML technologies to fit into our existing tech stack
- Solve idiosyncratic statistical, geometric, and engineering problems
- Work closely with a full‑stack tech team to assist implementation of research solutions into the product
- Contribute to hiring additional talent to our rapidly growing team
- Work with a broad tech stack (e.g. ReactJS, Python, REST & GraphQL, OpenCV, PyTorch, GCP, AWS & CUDA, Kubernetes) and the cutting edge of computer vision and deep learning
Who we're looking for:
- Hands‑on and experimental — you're comfortable executing on projects end‑to‑end, running tests, and iterating based on what the data tells you
- Collaborative by nature — you work closely with engineering and product teams to turn complex algorithmic ideas into reliable, scalable features
- Driven to solve hard problems — you thrive at the intersection of strong ML fundamentals and practical engineering
- Bonus: you've led or contributed to applied research teams and have relevant publications to show for it
Experience requirements:
- 3+ years of experience in machine learning engineering, with concrete examples of models or systems you've built and shipped
- Strong experience in Python and ML libraries such as OpenCV, PyTorch, TensorFlow, Fast.ai, and Keras
- Strong foundation in mathematical programming, algorithmic problem solving, and applied machine learning
- Bonus: experience in the AI/ML ecosystem and familiarity with computer vision
Why Encord:
- Competitive salary, commission, and meaningful equity in a high‑growth startup
- Strong in‑person culture — most of the team works from our London office 4+ days/week
- 25 days annual leave + UK public holidays
- Annual learning & development budget
- Travel for customer visits, events, and conferences across the UK and Europe
- Company lunches twice a week
- Monthly socials & bi‑annual team offsites
Machine Learning Engineer in London employer: Encord
Encord is an exceptional employer for Machine Learning Engineers, offering a dynamic work environment at the forefront of AI technology in London. With a strong emphasis on collaboration and innovation, employees benefit from competitive salaries, meaningful equity, and generous annual leave, alongside opportunities for professional growth through an annual learning budget and engaging team activities. Join a passionate team dedicated to solving complex problems and making a tangible impact in the AI landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Encord!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Machine Learning Engineer at Encord.
✨Leverage Professional Networks
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 Encord.
✨Apply Directly through Our Website
When you find a suitable opening like Machine Learning Engineer at Encord, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
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 Encord, 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 Encord. 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 Encord
✨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 Encord!
✨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.
