About us

Beat is one of the most exciting companies to ever come out of the ride-hailing space. One city at a time, all across the globe we make transportation affordable, convenient, and safe for everyone. We also help hundreds of thousands of people earn extra income as drivers. 

Today we are the fastest-growing ride-hailing service in Latin America. But serving millions of rides every day pales in comparison to what lies ahead. Our plans for expansion are limitless. Our stellar engineering team operates across a number of European capitals where, right now, some of the world’s most ambitious and talented engineers are changing how cities will move in the future.

Beat is currently available in Greece, Peru, Chile, Colombia, Mexico and Argentina. 

About the role

Working on Machine Learning at Beat, means you will work on high impact use cases across the domains of dynamic pricing, fraud detection, and dynamic dispatch with a strong focus on systems for making real-time decisions.

At Beat we do Machine Learning and Data Science with a product engineering mindset. In our Machine Learning chapter, you work with your colleagues in cross functional teams to translate product features into predictive modelling and machine learning problems. Exploratory analysis and hypothesis testing using the tools provided by Beat’s Big Data capabilities team help you build a deep understanding of the behaviour of our millions of daily users. You showcase how your models drive product features through rapid prototyping.

Then comes the best part: taking it to production. You care deeply about scalability and performance of training and inference. You work with other teams to productionise and monitor pipelines and setup telemetry data collection required to monitor your model in production. This way, you take on full ownership of your models running in production. 

Our remote workforce works East Europe Timezone hours (10am - 6pm) and therefore we will need you to be located within UTC to UTC+3 to reasonably overlap with your team members' work schedule. With the various tools and communication technologies we're using, you'll feel connected to your team. You always have the option to travel to our headquarters for meetings, events, and team bonding—or you can join virtually. Whatever works best for you and your work style.

About you

You are curious by nature, challenge assumptions, and naturally explore domain knowledge before jumping into solutions. You care about the real world context behind the data. As a strong communicator with business acumen you explain the essence of your modelling approach in business terms to product managers, designers, engineers, and other colleagues, while considering the implications of your solutions on Beat’s mission and bottom line.

You use your programming skills to automate workflows, build reproducible analyses, and deliver prototypes. Your tools of choice might include Python or R, as well as distributed computing on a Spark cluster, or running SQL queries against large datasets. Ideally, you are not afraid to dive into options like Scala for a high performance Spark job or perhaps Golang for a production service.

You can rigorously defend the maths and statistics behind your results and you have a working knowledge of the landscape of machine learning models and approaches, understanding their underpinning assumptions and implementation caveats.

You know that the life of a model only begins when it runs in production. You have a passion for the software engineering work behind computational performance, software architecture, and production monitoring of predictions and residuals. You continuously build the best experience for users whose day to day is affected by your prediction outcomes.

This job is for you if you:

• like big datasets, analysis, and modelling
• have a passion for coding
• want to build great products for urban travellers powered by machine learning

This job is not for you if you:

• think the leaderboard of a Kaggle competition is a better result than a model serving in production
• believe the modelling is a one time exercise and your code does not need to be maintained
• are not excited by working closely with other disciplines

What you need to bring 

• Solid understanding of methods, concepts, models, evaluation schemes across the whole DS/ML landscape, eg. supervised learning, unsupervised learning, data mining etc.
• Solid coding experience in Python.
• Solid experience in working the full software development lifecycle using the industry’s best practices. 
• Knowledge of SQL and relational databases. 

What is useful to have:

• Hands-on experience with MLOPs frameworks such as Kubeflow, MLFlow, (Azure ML Studio) or Amazon Sagemaker.
• Hands-on experience with Apache Spark.
• Hands-on experience with Docker and Kubernetes.

What's in it for you:

• Competitive salary package
• Flexible working hours
• High tech equipment and top line tools
• A great opportunity to grow and work with the most amazing people in the industry
• Being part of an environment that gives engineers large goals, autonomy, mentoring and creates incredible opportunities both for you and the company

As part of our dedication to the diversity of our workforce, Beat is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion.