Global scale ecosystem degradation is one of the world’s greatest challenges. At Dendra Systems, we are a fast-growing start-up enabling global scale management and restoration of natural ecosystems by developing the most powerful tools for ecosystem restoration today.
We’re looking for MLOps engineering talent to help us increase automation and improve the quality of production ML processes, and improve the quality and cycle time of our analytics.
● Productionising machine learning models
● Helping develop and maintain infrastructure to support ML model development, training and inference
● Porting workloads to use Ray Distributed and Ray Autoscaler
● Automate our data flows and reporting pipelines
● Improve our data lifecycles: create automated diagnostic reports for data quality, data drift, cycle times
● Assisting the machine learning scientists with their workflows
● Helping build, test, and release software with greater speed and frequency
● Tracking datasets and model artifact lineage and ensuring reproducibility
● Experienced Linux user
● Excellent Python programming skills
● Experience orchestrating tasks using frameworks such as AirFlow
● Experience deploying cloud services (bonus for AWS experience)
● Experience scaling workloads using distributed computing frameworks (especially PySpark, Ray Distributed)
Desired Skills and Experiences
● Experience with our stack: Ray Distributed, MLFlow tracking, Kedro
● Machine learning background, especially with PyTorch
● Containerization using Docker, Kubernetes
Preference will be given to candidates willing to work in the UK or Australia, but remote candidates are also being considered.
Dendra Systems believes that diversity builds strength, and this is already reflected in our international, interdisciplinary team. We look forward to building a strong team together.