Within the Cognition team, we are developing image recognition, NLP and Machine Learning models scalable to our marketplaces around the world. We develop a wide range of Machine Learning services: image classification, object detection, object segmentation and visual search, using recent CNN backbones and algorithms like YOLOv3. We are constantly analysing state-of-the-art models and papers to improve our solutions. Our Machine Learning tech stack is based on TensorFlow, Keras, Kubernetes and deployed on AWS Cloud.

Our teams are very autonomous and self organising; they are empowered to define the stack, approach to agile and architecture as a collective rather than from the top down.

Responsabilities:

• Selection of the right machine learning algorithm for business goals
• Build and implement highly scalable and reliable systems, using the best development practices and tools
• Experiment with different models and assess their potential in offline evaluations and by setting up A/B tests
• Collaborate in cross-functional teams consisting of product managers, data engineers and analysts to build a great search product that correspond to the needs of our marketplaces
• Contribute to the end-to-end deployment of high performing machine learning models to ensure it ends up in production as intended
• Help define our development environment and communicate the best development practices within the organization (i.e. code reviews, testing, etc)
• Continuously monitor the quality of our systems and models and design measurements to keep an eye on their health (both data quality and inference performance)
• Popularize image recognition initiatives via Medium posts and meetup talks and our internal community

At least Bachelor’s degree in Computer Science, Applied Mathematics, Statistics or any quantitative field.

We’re looking for someone interested in keeping abreast with machine learning and image recognition domain.

+4 years experience in industry in a similar role

• Experience applying machine learning modelling to create data products
• Experience with development in programming languages such as Java, Scala or Python
• Experience with TensorFlow and knowledge of state-of-the-art technologies in image processing and recognition
• Experience with setting up Machine Learning pipelines and training jobs as well as wrangling data from a variety of sources. e.g. csv, SQL, S3, etc.
• Proven track record of shipping technology while dealing with ambiguity, managing cross-team dependencies and relationships

What would be a plus:

• Experience with streaming tools such as Kafka and Spark Streaming
• Experience with AWS and/or other cloud providers
• Experience with microservices architectures and containers (using Docker, Kubernetes)

1. Practical case: real case ranking and NLP
2. Machine Learning Fundamentals: Machine Learning concepts
3. System Architecture: how to put models in production
4. Culture fit: culture fit with the team

Welcome on board!