Deskripsi Pekerjaan
Join Google's pioneering mission to eradicate mosquito-borne diseases through revolutionary AI solutions. As a Senior Software Engineer in our Machine Learning Debug team, you'll develop cutting-edge algorithms that predict disease outbreaks and optimize intervention strategies. This role offers the unique opportunity to apply advanced machine learning techniques to real-world humanitarian challenges while working with world-class engineers and researchers.
You'll be instrumental in building scalable systems that process vast datasets including satellite imagery, climate patterns, and human mobility metrics to create predictive models for diseases like dengue, Zika, and malaria. The position combines deep technical challenges with meaningful social impact, allowing you to directly contribute to global health initiatives while advancing the frontiers of AI technology.
Google offers an unparalleled environment for innovation, collaboration, and professional growth. You'll have access to state-of-the-art infrastructure and mentorship from industry leaders while contributing to projects that save lives and reshape public health approaches worldwide.
Tanggung Jawab
- Design, implement, and debug machine learning models for disease prediction and intervention optimization
- Develop scalable software solutions processing terabytes of geospatial and epidemiological data
- Collaborate with cross-functional teams including epidemiologists and data scientists
- Optimize ML pipelines for real-time deployment in diverse global environments
- Lead code reviews and establish best practices for ML system reliability
- Mentor junior engineers and contribute to technical documentation
- Research and integrate emerging ML techniques to enhance prediction accuracy
Kualifikasi
- Bachelor's degree in Computer Science, Engineering, or related field (Master's/PhD preferred)
- 5+ years of experience in software development with ML/AI focus
- Expertise in Python, C++, and distributed computing frameworks
- Proven experience with TensorFlow/PyTorch and large-scale ML deployment
- Strong background in debugging complex ML systems and performance optimization
- Experience with geospatial data processing and time-series analysis
- Ability to translate technical requirements into robust engineering solutions
- Excellent problem-solving skills and collaborative mindset