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Machine Learning Data Engineer, Associate
hace 2 meses
Cultivo Land is seeking a talented Machine Learning Data Engineer to join our team. As a Machine Learning Data Engineer at Cultivo, you will play a crucial role in developing and maintaining our data pipeline and infrastructure to support our machine learning projects. You will work closely with environmental scientists and software engineers to ensure efficient data collection, storage, and processing. This role offers a unique opportunity to contribute to impactful projects that are focused on regenerating ecosystems and addressing environmental challenges.
About Cultivo LandCultivo Land is a nature-focused fintech company with a mission to drive investment in regenerative land projects. Our work encompasses climate change, biodiversity, and land degradation. At Cultivo, we believe that by investing in nature, we can create a sustainable and resilient future. We have a diverse, collaborative, and inclusive work culture, and we offer flexible working arrangements to our team members.
Responsibilities- Designing, building, and maintaining scalable and efficient data pipelines and infrastructure for machine learning models
- Implement 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
- Stay updated with the latest trends and technologies in machine learning and data engineering
Requirements
Candidates should have …
- 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
Nice to have …
- 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
- Interest in environmental science and sustainability
Benefits
- The opportunity to grow as an Engineer and make a real impact around the world
- 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
