Machine Learning Engineer
Predictions and Market Modelling Team
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, the energy markets and society as a whole, thus enabling society to use the natural resources of our planet to the benefit of all.
Ingesting hundreds of rich data points per second from many vastly different external sources, moving terabytes of data while processing it in real-time, running complex and complicated 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 a highly reliable, stable, fault-tolerant infrastructure that can withstand multiple and varied uses and abuses by data analysts, data scientists, industry experts, and the end-users.
The Predictions and Market Modelling Team are responsible for generating high-value forecasts that enrich our data products. We have built a wide variety of Machine Learning models to predict the operations of the >10,000 tankers tracked by our system, which have enabled us to provide the most accurate and comprehensive view of global oil flows. Our ML models are continuously benchmarked and assessed by experienced market and data analysts to ensure the quality of our predictions. These models use a wide variety of technologies like Python/Numpy/Pandas/sklearn/Tensorflow, Java/Kotlin/Scala, Jupyter, Apache Kafka, Elastic Search, and AWS services like AWS Sagemaker, MSK, EKS, ECS, RDS, Athena, Airflow and others.
You’ll be instrumental in designing and building new infrastructure to propel the testing, deployment, and benchmarking of existing and new ML models. Working with data scientists, analysts, engineers and experts, 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 infrastructure. In addition to this, you’ll manage AWS costs, and work closely with team members to implement best practices in our key technologies.
- An expert in Python/Numpy/Pandas
- Experienced in Java or other JVM languages like Kotlin or Scala
- Experienced in building distributed systems, including real-time streaming and batch data processing
- An AWS power user and evangelist who can deploy and operate high-availability production systems
- Are skilled with Kubernetes
- Not afraid of challenges and infrastructure troubleshooting
- Excited about working in a start-up environment
- Motivated by bringing new ideas to production
- Self-sufficient but not afraid to ask for help when needed
- A thinker who likes to push the boundaries of their job role
Awesome If You:
- Have experience with Apache Kafka and Kafka Streams – deployment, monitoring, resiliency, fault-tolerance, cluster planning and operations, applications debugging
- Have experience with Machine Learning research and development projects
- Proficient in Terraform, bash scripting
- Are familiar with Airflow or other workflow orchestration tools
- Have some relevant AWS or Kafka certifications
- Understand data lakes like Parquet, Orc, Athena
- 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, which all of us are – in a business-savvy and responsible way
- Enjoying a friendly working environment
- Motivated by being collaborative, working and achieving together
- Not only teammates but friends, often finishing the week enjoying a glass of a favourite drink and a game of 3D Connect 4 together
- Offering a generous salary and equity
Interested? Tell us about yourself by contacting Jessica at email@example.com!