Get started with your online application
Not quite your dream role? Sign up to get notified when the right vacancy comes along.
Machine Learning Engineer
The Data + Science Team
At Deliveroo we have a world-class data & science organisation, with a mission to enable the highest quality human and machine decision-making. We have over 200 Machine Learning Engineers, Data Scientists, Data Analysts, and Analytics Engineers working throughout the company in product, business and platform teams.
We have a strong, active data science community, with guest lecturers; a robust technical review process; a career progression framework; and plenty of opportunities to learn new things.
The Role
We are hiring several MLE positions in different teams across all sides of our marketplace (consumer, delivery, restaurants, grocery, and retail). Our interview process is team-agnostic.
As an MLE, you will develop the algorithmic and machine-learning systems that power Deliveroo. You will work in a cross-functional team alongside engineers, data scientists and product managers to develop systems that make automated decisions at massive scale. Your team has independence and works at some of the most interesting problems at the intersection of our three-sided marketplace (riders, consumers, and restaurants). We evaluate the performance of all our decision-making machines through our world-class experimentation platform.
Depending on the team you join, you will build intelligent decision-making machines that may:
Optimise our delivery network by making rider assignment decisions; predicting how long a leg of the delivery journey will take; or mitigating real-time delays.
Work out how many riders we need in a particular place at a particular time.
Optimise consumer and rider fees.
Improve the consumer experience by showing the most relevant restaurants and dishes.
Detect fraud and abuse from consumers, riders, and restaurants.
Assist restaurants in optimising their presence on Deliveroo, for example by recommending that they improve their menus or photography, or add a popular dish.
Requirements
3+ years' experience as a ML Engineer or Data Scientist
3+ years' experience in Python
Experience productionising ML models
Experience using tools like Git, Docker, Kubernetes, CircleCI
You know the fundamentals of machine learning and when they should be applied
You can translate an unstructured business problem into a well-thought-out algorithmic solution
You get satisfaction from seeing your algorithms shipped and driving measurable impact to the business
You have a bias to simplicity, where you care most about achieving impact
The Company
Our mission is to be the definitive food company. We are transforming the way the world eats by making food more convenient and accessible. We are a technology-driven company at the forefront of the most rapidly expanding industry in the world. We are still a small team, making a very large impact, looking to answer some of the most interesting questions out there. We move fast, value autonomy and ownership, and we are always looking for new ideas.
At Deliveroo we know that people are the heart of the business and we prioritise their welfare. Benefits differ by country, but we offer many benefits in areas including healthcare, well-being, parental leave, pensions, and generous annual leave allowances, including time off to support a charitable cause of your choice. Benefits are country-specific, please ask your recruiter for more information.
Diversity
At Deliveroo, we believe a great workplace is one that represents the world we live in and how beautifully diverse it can be. That means we have no judgement when it comes to any one of the things that make you who you are - your gender, race, sexuality, religion or a secret aversion to coriander. All you need is a passion for (most) food and a desire to be part of one of the fastest-growing businesses in a rapidly growing industry.
We are committed to diversity, equity and inclusion in all aspects of our hiring process. We recognise that some candidates may require adjustments to apply for a position or fairly participate in the interview process. If you require any adjustments, please don't hesitate to let us know. We will make every effort to provide the necessary adjustments to ensure you have an equitable opportunity to succeed
A competitive and comprehensive compensation and benefits package
1
Compensation
- We aim to pay every employee competitively for the role they are performing in their respective location
- Depending on role and location, some employees may be eligible for an annual cash bonus, sign-on bonus or relocation support
- Up to 5% matched pension contributions
2Equity
- Some roles may be eligible for share awards, giving them ownership in Deliveroo and a share in our success
3Food
- Free Deliveroo Plus: free delivery and access to special offers
- Team lunches from the best local restaurants
4Time away
- 25 days annual leave plus bank holidays, increasing with length of time spent working at Deliveroo
- One day of paid leave per year to volunteer with a registered charity
5
- Funded single cover healthcare on our core plan, with the option to add family members at own cost
- On-site gym (HQ), discounted external gym membership
- Access to wellbeing apps such as LesMills+, Strava, Headspace, Yogaia via GymPass
- Discounted dental insurance and a range of other flexible benefits, such as critical illness cover, partner life cover, travel insurance, health assessments
- Life assurance
6Work Life
- Maternity, paternity and maternity and shared parental leave, eligible from day one of employment
- Excellent kit to enable working from home and a parent-friendly working culture
- Access to free mortgage advice
- Cycle to Work Scheme or Season Ticket Loans, depending how you wish to travel
- Excellent learning and development opportunities and access to RooLearn, our learning platform, packed with high-quality training and content
- Regular Employee Resource Group (ERG) led social events – examples include dinners, dance lessons and in-office yoga sessions
#J-18808-Ljbffr
:quality(80))
:quality(80))
:quality(80))