Vortexa

Vortexa is a fast-growing international technology business 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. 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 Platform Team is responsible for all of Vortexa's data. The team's ownership ranges from raw satellite AIS/imaging data to unstructured textual and graphical maritime data like fixtures, port lineups, and customs filings. The team is also responsible for highly structured datasets such as price and supply-demand forecasts as well as modeling the global energy flows and tanker fleet distributions. 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. 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 flows of oil and fuels in real-time, optimising the energy markets and enabling the society as a whole to use the natural resources of our planet to the benefit of all. You Are: Fluent in Python and software engineering fundamentals, and comfortable with highly scalable data processing libraries Strong expertise in distributed systems, micro-service architectures and scalable data processing pipelines Driven by working in an intellectually engaging environment with the top minds in the industry, where constructive and friendly challenges and debates are encouraged, not avoided Excited 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 role Experienced in building distributed heavy-load backend systems that can go through terabytes of data daily Passionate about coaching developers, helping them improve their skills and grow their careers Deep experience of the full software development life cycle (SDLC), including technical design, coding standards, code review, source control, build, test, deploy, and operations Awesome If You: Are experienced in Rust / Java / Kotlin Have experience with AWS, Apache Kafka, Kafka Streams, Apache Beam / Flink / Spark - especially deployment, monitoring & debugging Have experience with productisation of Machine Learning research projects Are familiar with Airflow or other workflow orchestration tools, and worked with Kubernetes Understand data lake systems and file formats like Parquet, Orc, Athena Have some relevant AWS or Kafka certifications A vibrant, diverse company pushing ourselves and the technology to deliver beyond the cutting edge A team of motivated characters and top minds striving to be the best at what we do at all times Constantly learning and exploring new tools and technologies Acting as company owners (all Vortexa staff have equity options) in a business-savvy and responsible way Motivated by being collaborative, working and achieving together A flexible working policy- accommodating both remote & home working, with regular staff events Private Health Insurance offered via Vitality to help you look after your physical health Global Volunteering Policy to help you 'do good' and feel better

Vortexa, a fast-growing technology company in Greater London, is seeking a skilled developer to design and build scalable data pipelines and applications. Candidates should be fluent in Python, experienced with distributed systems and excited about working in a dynamic startup environment. Responsibilities include ensuring the uptime of data pipelines and collaborating with data scientists. The position offers private health insurance, flexible working arrangements, and opportunities for professional growth.

Processing thousands of energy data points per second from diverse operational sources, handling massive volumes of energy data while running sophisticated classification and anomaly detection models in real-time, maintaining comprehensive data lineage, and delivering insights through high-performance platforms used by energy operators globally requires exceptional engineering and scientific expertise. This processing demands models that can withstand the scrutiny of energy analysts and traders, operations teams, and regulatory bodies, with the performance, stability, and reliability that critical energy systems require. The Data Platform Team is responsible for all machine learning operations across our energy data ecosystem. We work with everything from raw sensor data from millions of energy assets to complex operational datasets, generating high-value predictions such as equipment failure detection, energy demand forecasting, operational anomaly identification, predictive maintenance scheduling, and system optimization recommendations. The team has built a comprehensive suite of statistical and machine learning models that enable us to provide the most accurate and actionable insights into energy operations. We take pride in applying cutting edge research to real world energy challenges in a robust, scalable, and maintainable way. The quality of our models is continuously validated by experienced in house energy analysts and traders and domain experts to ensure reliability of our predictions. You'll be instrumental in designing and building ML infrastructure and applications to propel the design, deployment, and monitoring of existing and new ML pipelines and models. Working with software engineers, data scientists, and energy analysts and traders, you'll help bridge the gap between research experiments and production energy systems by ensuring 100% uptime and bulletproof fault tolerance of every component of our ML platform. You Are: Experienced in building and deploying distributed scalable ML pipelines that can process large volumes of energy data daily using Kubernetes and MLflow With solid machine learning engineering fundamentals, fluent in Python, PyTorch, and XGBoost Skilled in developing classification models and anomaly detection systems for production environments Capable of implementing comprehensive data lineage tracking and model governance systems Driven by working in an intellectually engaging environment with top energy analysts and traders and technology experts, where constructive challenges and technical debates are encouraged Excited about working in a dynamic environment: not afraid of complex energy challenges, eager to bring new ML innovations to production, and a positive can do attitude Passionate about mentoring team members, helping them improve their ML engineering skills and grow their careers Experienced with the full ML model lifecycle, including experiment design, model development, validation, deployment, monitoring, and maintenance Awesome If You: Have experience in the energy sector or understanding of energy systems and operations Have practical experience with AWS services (SageMaker, S3, EC2, Lambda, etc.) Have experience with infrastructure as code tools (Terraform, CloudFormation) Have experience with Apache Kafka and real time streaming frameworks Are familiar with observability principles such as logging, monitoring, and distributed tracing for ML systems Have experience with transformer architectures and generative AI applications in operational contexts Have experience with time series analysis and forecasting techniques relevant to energy applications Are knowledgeable about data privacy regulations and compliance frameworks in the energy sector Benefits Enjoy flexible hybrid working - split your time between home and our office, with the freedom to work where you're most productive. A vibrant, diverse company pushing ourselves and the technology to deliver beyond the cutting edge A team of motivated characters and top minds striving to be the best at what we do at all times Constantly learning and exploring new tools and technologies Acting as company owners (all Vortexa staff have equity options)- in a business savvy and responsible way Motivated by being collaborative, working and achieving together Private Health Insurance offered via Vitality to help you look after your physical health Global Volunteering Policy to help you 'do good' and feel better