In a world where trades are happening faster than ever to answer our needs, where sustainability is not just an option anymore, clarity and trust in the information we trade with are a must.
So, say hello to Kpler! We exist to facilitate sustainable and efficient trade to meet the changing needs of our world(e)To do so we've built a Data-as-a-Service solution that does exactly that across the lifecycle of a trade.
Our solution aggregates data from hundreds of sources including radar and satellite imagery as well as logistics, governmental, shipping databases and more(e)Intelligently connecting the dots across fragmented information landscapes, we bring to our clients a unique, real-time understanding of the trades happening all over the world, by giving them access to live information about the movement of cargos, the availability of vessels as well as the commodity storage.
To support this endeavor we have teams in more than 7 countries and 8 key locations (Brussels, Paris, London, Vienna, Dubai, Singapore, Houston and New York)(e)With individuals of various backgrounds, diverse skills, and international experiences, being global & inclusive is in our DNA!
Our values
• Be humble - We always place the interests of the collective before your own.
• Respect and care for others - We make every person feel comfortable in their own beliefs, decisions, and perspectives.
• Take responsibility - We take ownership of our actions
• Act with integrity -We are honest and transparent in all your dealings.
• Be bold - We push the boundaries in order to improve and grow.
You’ll get to work in a truly global environment, with more than 30 nationalities speaking more than 15 languages.
About the job
Building machine learning production infrastructure (or MLOps) is the biggest challenge most large companies currently face in making the transition to becoming an AI-driven organization(e)This position is an opportunity for an experienced MLOps engineer to grow into developing state of the art machine learning production systems and pipelines at Kpler.
Responsibilities
* Design the data pipelines and engineering infrastructure to support our machine learning systems at scale
* Take offline models data scientists build and turn them into a real machine learning production system
* Develop and deploy scalable tools and services to handle machine learning training and inference
* Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems
* Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
* Support model development, with an emphasis on versioning and data security and integrity
* Facilitate the development and deployment of proof-of-concept machine learning systems
* Communicate with data scientists to build requirements and track progress
Qualifications and technologies required
* Machine Learning automation
* Python
* SQL
* Airflow
* SageMaker (AWS)
* Feature Store (any vendor)
* ML monitoring
Nice to have
* TensorFlow, PyTorch, LightGBM, XGBoost
* Kubernetes
* Kafka
* Datadog
#LI-Remote
Our People Pledge
Kpler is committed to providing a fair, inclusive and diverse work-environment(e)We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community(e)We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.