At a Glance
- Tasks: Design and deploy intelligent systems to tackle real-world challenges at Picnic.
- Company: Join Picnic, a fast-growing startup revolutionising grocery delivery across Europe.
- Benefits: Enjoy fresh lunches, health insurance discounts, and a supportive work environment.
- Why this job: Make a visible impact while working with cutting-edge technology in a diverse team.
- Qualifications: Master's degree in AI or related field and 5+ years of machine learning experience.
- Other info: Experience a vibrant culture with fun activities and excellent career growth opportunities.
The predicted salary is between 48000 - 72000 £ per year.
As a Machine Learning Engineer at Picnic, you will design and deploy intelligent systems to solve our company’s biggest challenges. Beyond building models, you will productionize them with strong monitoring and seamless integration into operational systems. You will collaborate closely with stakeholders to ensure the right problems are solved and that solutions deliver real-world impact, all using high quality data. Our data is registered, logged, and consistent, enabling you to focus on building and improving models rather than cleaning data. This role combines the skills of a consultant, software engineer, and applied mathematician.
You will definitely:
- Identify and execute improvement possibilities together with other ML Engineers and (product) analysts
- Collaborate on your project from inception to production, to continuous improvement
- Develop tools and enhancements for our cloud-based Machine Learning platform
You could work on various projects and fields, such as:
- Demand forecasting: delivery, article, trip volumes, used Picnic-wide
- Fraud detection: helping us keep troublemakers out of our store
- Recommendation systems: generating useful in-app grocery suggestions
- Search and ranking: helping our customers find exactly what they need
- Predicting delivery drop-off times: making sure we’re on-time at every customer’s door
- Vision: ensuring quality control and smooth operations within our warehouses
Requirements:
- Master’s degree or higher in AI, Computer Science, Mathematics, or a related field
- 5+ years of experience in data science or applied machine learning
- Excellent communication skills, you can clearly explain complex ideas in non-technical terms and enjoy working closely with business stakeholders to solve problems together
- Experienced in designing, deploying, and maintaining production ML systems, with solid software engineering and ML principles
- Strong Python and SQL skills
- Able to define the long-term vision and technical architecture for ML solutions within your domain
- Experience with Docker, Kubernetes, and CI is a plus
Picnic Perks:
- Teamwork makes the dream work: With more than 80 nationalities across 3 countries, you’ll be part of a diverse company with plenty of cool stuff to get involved with, from board game evenings to after-work drinks to our company ski trip and more!
- Make a difference: You’ll work in an awesome startup environment with the freedom to drive your own projects and create a visible impact. Our fully electric vehicles and sustainable business model mean you’ll also be contributing to making the world a better place!
- Fresh Lunch, coffee, and snacks: Our offices are equipped with fully-fledged coffee bars and a kitchen and chefs. They prepare delicious fresh and warm lunches every day so you can keep your energy up.
- We have a partnership with CZ (a health insurance provider). Picnic employees get a discount on CZ insurance packages between 5% and 15%. Furthermore, through our partnership with Lease a Bike, you can rent-to-own a new (e)bike at a discounted rate.
- If you’re moving from another country to join Picnic we make it as smooth as possible for you. We’ll cover your flight costs for you and your partner and kids, your first month's rent and moving costs (up to €2000), and help you with the 30% tax ruling setup and application.
- At Picnic you get 25 holidays, we cover your travel expenses and offer a pension plan. And your phone and laptop are on us, as well.
A bit about us: When you join Picnic, you’re joining the shopping revolution, delivering groceries to millions of people across Europe, and we’re growing fast. Think super fresh products and personal service, but in a modern, sustainable way. The tech team at Picnic is at the core of Picnic. From deep learning models to forecast orders to delivery algorithms to warehouse logistics: we’ve built it all from the ground up. You’ll thrive here if you’re a problem solver with a pro-active mindset who’s not afraid to be challenged daily.
Commitment to equal opportunities: Picnic is an equal opportunity employer—this means that all decisions regarding applications will be based on qualifications and merit. Applicants will be regarded independently of age, gender identity or expression, sexual orientation, ethnicity, skin color, civil status, religious beliefs, physical or mental disability, or any other factors protected by law. At Picnic, we celebrate and value our differences and are committed to building a safe and inclusive working environment where everyone can be themselves.
Senior Machine Learning Engineer in London employer: Picnic Technologies
Contact Detail:
Picnic Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Picnic on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your best machine learning projects. When you get the chance, share how you've tackled real-world problems with your models.
✨Tip Number 3
Ace the interview by being ready to discuss your thought process. Be prepared to explain complex ideas in simple terms, just like you would to a business stakeholder.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Picnic team.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with production ML systems and any relevant projects you've worked on. We want to see how your skills align with our needs!
Showcase Your Communication Skills: Since you'll be collaborating closely with stakeholders, it's crucial to demonstrate your ability to explain complex ideas in simple terms. Use examples in your application that showcase your communication prowess.
Highlight Relevant Experience: Don’t forget to mention your experience with Python, SQL, Docker, and Kubernetes. These are key skills for us, so make them stand out in your application. We love seeing candidates who can hit the ground running!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, we can't wait to hear from you!
How to prepare for a job interview at Picnic Technologies
✨Know Your Models Inside Out
Make sure you can discuss your previous machine learning projects in detail. Be ready to explain the models you built, the challenges you faced, and how you overcame them. This shows your depth of knowledge and experience, which is crucial for a Senior Machine Learning Engineer role.
✨Brush Up on Communication Skills
Since you'll be collaborating with stakeholders, practice explaining complex technical concepts in simple terms. Prepare examples of how you've successfully communicated with non-technical team members in the past. This will demonstrate your ability to bridge the gap between tech and business.
✨Familiarise Yourself with Their Tech Stack
Research Picnic's use of Python, SQL, Docker, and Kubernetes. If you have experience with these technologies, be prepared to discuss specific instances where you've used them. Showing that you're already familiar with their tools will give you an edge.
✨Prepare for Problem-Solving Scenarios
Expect to face real-world problem-solving scenarios during the interview. Think about how you would approach challenges like demand forecasting or fraud detection. Practising these scenarios will help you articulate your thought process and showcase your analytical skills.