Remote | Machine Learning Engineer (Search)

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

The Data Science team at OLX Group is responsible for building algorithmic solutions to facilitate transactions between buyers and sellers. We are developing personalization technologies and optimization strategies that have a direct impact on OLX’s users as well as the company’s bottom line.

You will be encouraged to research state-of-the-art machine learning, in the areas of search relevance, ranking, recommender systems, and more. Applying these methods to core OLX product platforms deployed in the cloud that are affecting the user experience for millions of visitors per month, rolling your solutions to production, analyzing model results offline and online, and measuring site impact.

Some of the challenges that we are focusing on are maximizing the relevance of the search results by applying ML-based rankers, combining different sources of ads in search and recommendations to optimize the satisfaction of both buyers and sellers, estimating the impact that the interactions generated by the buyers have on the revenue, and detecting trending products even before they become popular.

The team

The Data Science Buyer team at OLX Group is responsible for unlocking the hidden value for our users by using data and artificial intelligence. Our main goal is to help our customers to find the best products in an efficient and enjoyable way. We have a track record of impactful applications of ML to solve business problems in some of the main user flows and we want to continue expanding the boundaries of what ML is capable of at OLX. 

Our team collaborates with product teams from OLX, as well as the Motors and Real Estate verticals like Otomoto and Otodom, across the entire EU region. This means that our solutions need to scale to millions of data points and may be reused in markets with similar characteristics. We think of experimentation as a tool to learn what our users want. We always start simple and fail fast. This way we can create solutions that can be adapted to every market.

Right now, we're hiring a mid-level Machine Learning Engineer. On a typical day, you will be implementing machine learning pipelines and taking our ML solutions to a production-ready state. You will collaborate with data scientists in all the stages of an ML project, starting from data extraction to preprocessing, training, evaluating and serving the predictions to our end-users. You will work with engineers to monitor our models, make our ML services fault-tolerant, optimise performance and cloud costs. In any case, you will find a group of friendly people that wants to collaborate with you to improve the user experience and ultimately have fun together!

What you will be doing:

• Work in multi-functional teams with people from different backgrounds
• Build effective solutions with machine learning
• Collaborate with Data Scientists and SREs to bring machine learning services to production
• Measure the impact of your models on company goals
• Collaborate with internal and external stakeholders
• Drive data science efforts across the organization

Your skills and experience:

• At least 2 years of professional experience as a machine learning engineer
• Experience participating in projects related to search relevance and ranking
• Good knowledge of the best engineering practices
• Experience bringing machine learning models into production
• Strong engineering background: excellent knowledge of Python, exposure to other programming languages (Kotlin, Java, etc)
• Experience in using machine learning frameworks in production settings: Scikit-Learn, TensorFlow (or similar)
• Good understanding of machine learning basics

Nice to have:

• Experience with serving machine learning models at scale
• Solid understanding of AWS and experience using AWS for deploying machine learning solutions
• Experience with building data pipelines using tools like Spark and Airflow
• Exposure to production infrastructure and best DevOps practices: monitoring, alerting, CI/CD, container-orchestrating platforms, and infrastructure-as-code tools (Grafana, Prometheus, Kubernetes, Terraform)

What we offer:

• Permanent contract.
• Annual bonus of 15% of your base salary.
• Strengths-based personal career development.
• Company mobile phone, MacBook Pro or Windows Dell along with necessary accessories to make your work comfortable.
• Competitive compensation and benefits (medical care, sports package and others).
• Training and conference budget.
• The opportunity to learn from each other and become better every day.
• A passionate and diverse team of data scientists spanning across several tech hubs in Europe and around the world.