Apollo Agriculture
Senior Machine Learning Engineer
Hybrid
Full Time
#Engineering
#Python
#Java
#Golang
#Scala
#AWS
#ECS
#Sagemaker
#Machine Learning
#Cloud Computing
Apollo Agriculture is looking for a Senior Machine Learning Engineer
Full TimeSeniorHybridNetherlandsEngineeringPythonJavaGolangScalaAWSECSSagemakerMachine LearningCloud ComputingEnglishHybrid work
Apollo Agriculture is a commercial farming platform dedicated to helping small-scale farmers significantly increase their profitability. By utilizing machine learning to power credit models and automated operations, we unlock the potential of the small-scale farming market. Our team is composed of experts from organizations like Google, The Climate Corporation, and Booking.com, and we are looking for a Senior Machine Learning Engineer to join our Data Science team in the Netherlands on a hybrid basis.
Responsibilities
- Develop machine learning models that enhance our product and improve the customer lifecycle.
- Design and deploy scalable systems to meet our increasing operational demands.
- Manage and improve our cloud-based machine learning platform, focusing on feature engineering, model development, and production training.
- Identify and evaluate new opportunities to integrate machine learning across our business.
- Provide mentorship to peers and engineers to help them effectively apply machine learning techniques.
- Work closely with our product, engineering, and credit teams to refine our fraud detection, credit decisioning, and advisory tools.
Must-haves
- At least 3 years of experience in a machine learning engineering or data science role, with a focus on maintaining model pipelines and ML platforms.
- 5 or more years of professional software development experience at a fast-growing technology company, with proficiency in Python, Java, Golang, or Scala.
- At least 1 year of experience with AWS cloud infrastructure, specifically using ECS and Sagemaker to build and deploy models.
- Strong communication skills, with the ability to translate complex technical challenges into clear documentation and proposals.
- A creative, hands-on approach to problem-solving, especially when working with limited datasets or challenging infrastructure environments.
- Fluency in English.
Benefits
- Hybrid work environment.
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