🚀 Internship

Data Engineer, Industrial Placement/Graduate- Summer/Sept 2023 start


3mo ago

🚀 Placement Program


Rolling basis


Vortexa was founded to solve the immense information gap that exists in the energy industry. By using massive amounts of new satellite data and pioneering work in artificial intelligence, Vortexa creates an unprecedented view on the global seaborne energy flows in real-time, bringing transparency and efficiency to the energy markets and society as a whole.

The Challenge

Processing thousands of rich data points per second from many vastly different external sources, moving terabytes of data while processing it in real-time, running complex prediction and forecasting AI models while coupling their output into a hybrid human-machine data refinement process and presenting the result through a nimble low-latency SaaS solution used by customers around the globe is no small feat of science and engineering. This processing requires models that can survive the scrutiny of industry experts, data analysts and traders, with the performance, stability, latency and agility a fast-moving startup influencing multi-$m transactions requires.

The Data Production Team is responsible for all of Vortexa’s data. It ranges from mixing raw satellite data from 600,000 vessels with rich but incomplete text data, to generating high-value forecasts such as the vessel destination, cargo onboard, ship-to-ship transfer detection, dark vessels, congestion, future prices, etc

The team has built a variety of procedural, statistical and machine learning models that enabled us to provide the most accurate and comprehensive view of energy flows. We take pride in applying cutting-edge research to real-world problems in a robust, long-lasting and maintainable way. The quality of our data is continuously benchmarked and assessed by experienced in-house market and data analysts to ensure the quality of our predictions.

You’ll be instrumental in designing and building infrastructure and applications to propel the design, deployment, and benchmarking of existing and new pipelines and ML models. Working with software and data engineers, data scientists and market analysts, you’ll help bridge the gap between scientific experiments and commercial products by ensuring 100% uptime and bulletproof fault-tolerance of every component of the team's data pipelines.

View more

Area of Responsibilities



Learning opportunitiesYou will be considered an integral part of a team of 3-5 engineers and data scientists, and will contribute to delivering the same goals & roadmap as everyone around you. By working on the same projects as everyone else, you will get prompt and thorough support and feedback: we believe this is the best way to maximize your learning and impact.Our goal is to identify and nurture promising talent: it is in our best interest to help you be successful, and if there is a fit you’ll be first in line for hiring.The role offers the opportunity to help with and lead projects on:Data engineering: extracting, transforming and loading data at scaleMachine learning: prototype, improve and productionalise algorithms making inferences, at scaleBusiness: interact with experts from the energy industry, and observe and influence a start-up getting a lot of market traction and reacting to itKey technologies you will use:Programming: Python, SQL and some Rust / Java / KotlinCloud: AWSCompute: Docker containers running on KubernetesOrchestration: Airflow and KafkaStorage: S3 and PostgresFor placements of more than 6 months, you’ll be offered to change teams halfway through your placement.
View more


Fluent in software engineering fundamentalsDriven by working in an intellectually engaging environment with the top minds in the industry, where constructive and friendly challenges and debates are encouraged, not avoidedExcited about working in a start-up environment: not afraid of challenges, excited to bring new ideas to production, and a positive can-do will-do person, not afraid to push the boundaries of your job roleFluent in Python, and comfortable with Pandas / Numpy
View more