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Senior Machine Learning Engineer

Details of the offer

The Data & Science Org
At Deliveroo, we have a world-class data science organisation with a mission to enable the highest quality human and machine decision-making. We work throughout the company - in product, business and platform teams to answer some of the most interesting questions out there. For example, how do data and technology help restaurants to grow as consumer habits change? How can we predict what someone wants to order for dinner long before the idea has even crossed their mind? At Deliveroo, these are just some of the tough problems we are solving - and there is no challenge that cannot be yours.
Data Scientists and ML Engineers at Deliveroo report to our data science management team, and 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.
As a Senior Machine Learning Engineer, you will play a crucial role in the development and implementation of cutting-edge artificial intelligence products. Your responsibilities will involve designing and constructing sophisticated machine learning models, as well as refining and updating existing systems. In order to thrive in this position, you must possess exceptional skills in statistics and programming, as well as a deep understanding of data science and software engineering principles.

The Ads ML Team
We are part of the cross-functional Ads Tech at Deliveroo, a group of 20+ passionate engineers, scientists, and machine learning engineers who focus on building our internal Ad Platform, where our Partners can advertise their restaurants.
The Ads ML Team is responsible for recommending sponsored content on Deliveroo. The team strives to push the boundary of what's possible in this space, working on Click-Through-Rate estimation, Automated Bidding, Budget Recommendation and Dynamic Ads Load. Apart from excelling in complex prompt engineering, there will be a focus on developing in-house models and auction simulators, deploying models in production, and improving ML model monitoring and alerting.
We evaluate the performance of all our decision-making machines via robust experimentation powered by our world-class experimentation platform.
You will report into a Machine Learning Engineer. This is a hybrid role that can be based in either Hyderabad or Bengaluru, with some expectations to come into the office.

What You'll Do
Work in a cross-functional team alongside engineers, data scientists specialised in analytics and inference, and product managers to develop systems that make automated decisions at a massive scale
Use frameworks such as Tensorflow to build new and improve existing machine learning models for sponsored content recommendation, automated bidding, budget recommendation, and dynamic ad load
Automate training and inference pipeline using job orchestrating frameworks such as Argo Workflow.
Mentor and coach team members on ML engineering best practices

Requirements
A master's degree in Computer Science, Mathematics, or a related quantitative discipline
5+ years' experience deploying machine learning models at scale in production environments
Proficiency in writing production-quality Python code
Familiarity with Python data science and machine learning libraries, including scikit-learn, TensorFlow, Keras, pandas, numpy, and XGBoost
Thorough understanding of best practices in MLOps
Sound knowledge of the machine learning application development life cycle, encompassing CI/CD, version control (git), testing frameworks, MLOps, agile methodologies, monitoring, and alerting
Hands-on experience in operationalising ML models and constructing ML pipelines
Proficient in exploratory data analysis, model/algorithm prototyping and selection, and model pipeline design and development
Practical experience with AWS or a comparable cloud service provider
Comfortable working with Docker and containerised applications
Familiarity with Git, GitOps practices, Argo Workflow, etc.
Familiarity with CI/CD tools such as Jenkins, CircleCI, GitHub Actions, etc.
Strong collaborative skills, able to work alongside scientists, engineers, and non-technical stakeholders
A bias for simplicity and impact
Experience developing Click-Through-Rate estimation and automated bidding models

Why Deliveroo
Our mission is to transform the way you shop and eat, bringing the neighbourhood to your door by connecting consumers, restaurants, shops and riders. . We are transforming the way the world eats and shops by making access to food and products more convenient and enjoyable. We give people the opportunity to buy what they want, as they want it, when and where they want it.
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.
Workplace & Benefits
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.


Nominal Salary: To be agreed

Source: Greenhouse

Requirements

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