Cultivo is hiring a
Machine Learning Data Engineer

Summary

Cultivo Land is seeking a Machine Learning Data Engineer to develop and maintain data pipelines for machine learning projects. The role involves collaboration with environmental scientists and software engineers, and offers opportunities for personal and professional growth in an innovative and supportive environment.

Requirements

• 2+ years of experience as a data engineer, machine learning engineer, or related role
• Strong programming skills in Python
• Experience with SQL and Big Data technologies such as GCP Bigquery, Streaming services, etc
• Knowledge of machine learning concepts and algorithms
• Experience with data preprocessing, feature engineering, and analysis
• Strong problem-solving and analytical skills
• Experience with data visualization tools
• Comfort working in a fully remote, distributed, global team

Responsibilities

• Designing, building, and maintaining scalable and efficient data pipelines and infrastructure for machine learning models
• Implementing data collection and feature engineering processes in Google Cloud Platform (GCP)
• Collaborating with data scientists and engineers to implement and deploy machine learning models
• Managing and optimizing data storage and retrieval systems (BigQuery, Dataflow, Vertex AI)
• Performing data preprocessing, feature engineering, and analysis
• Monitoring and optimizing data pipelines for performance and reliability
• Ensuring data quality and implementing data governance best practices
• Staying updated with the latest trends and technologies in machine learning and data engineering

Preferred Qualifications

• Bachelor’s degree or above in Computer Science, Data Science, or a related field
• Experience with cloud platforms such as GCP
• Experience with geospatial data
• Knowledge of deep learning frameworks such as TensorFlow or PyTorch

Benefits

• Competitive compensation package, including equity options and annual bonus
• Access to health insurance and retirement plan
• Remote-first setup, with flexible, cadenced in-person co-working days alongside hub-based teammates
• Flexible work hours with emphasis on results
• International office locations
• 6 months paid parental leave
• Flexible paid vacation
• Opportunities for personal and professional growth in an innovative and supportive environment