Senior Machine Learning Engineer
hace 1 semana
Kilimo is seeking a Senior Machine Learning Engineer with a strong background in deploying and scaling machine learning models. The ideal candidate will bring extensive experience in building and maintaining ML pipelines, along with a deep understanding of modern machine learning frameworks, particularly in applications related to climate and agricultural domains.
Key Responsibilities
Model Development and Deployment- Design, build, and optimize scalable machine learning models for climate and agricultural applications.
- Implement production-ready ML pipelines, including feature engineering, model training, and evaluation.
- Deploy and monitor models in production to ensure performance and reliability.
- Develop automated systems for model retraining, versioning, and monitoring.
- Integrate CI/CD workflows into ML pipelines to streamline development and deployment.
- Collaborate with Data Engineers to ensure seamless integration of models into larger systems.
- Apply machine learning techniques to analyze climate, weather, and agricultural data.
- Develop predictive models for crop growth, irrigation optimization, and environmental sustainability.
- Utilize remote sensing data and satellite imagery for geospatial analysis and decision-making.
- Stay updated on the latest trends in machine learning and apply state-of-the-art techniques.
- Optimize models for performance, scalability, and accuracy in large-scale deployments.
- Conduct experiments to test and validate hypotheses for ML-driven solutions.
- 5+ years of experience in Machine Learning Engineering or a related field.
- Strong programming skills in Python and familiarity with frameworks like TensorFlow, PyTorch, or scikit-learn.
- Hands-on experience with ML pipeline tools (e.g., MLflow, Kubeflow, Airflow).
- Proficiency in cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Knowledge of climate science, agronomy, or related fields.
- Familiarity with datasets such as satellite imagery, weather patterns, or agricultural productivity metrics.
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.
- Advanced certifications in Machine Learning, MLOps, or related areas are a plus.
- Proven ability to design and implement efficient solutions for complex problems.
- Experience in optimizing machine learning workflows for performance and scalability.
- Familiarity with geospatial analysis and remote sensing technologies.
- Experience with big data frameworks (e.g., Apache Spark) is a plus.
- Understanding of ethical AI principles and practices.
Commitment to Impact
This role is ideal for professionals who are passionate about leveraging machine learning to advance sustainability and innovation in climate-smart agriculture.
- Work in an international company with global expansion.
- Remote work and flexible hours.
- Training program: we support you in pursuing education and skills development in areas that interest you.
- Competitive salary and family health plan.
- We’re proud to be recognized as a Great Place to Work for the 4th year in a row
- Analyze data to help create a future with water available for communities, ecosystems, and economic development
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