Job Description:
Machine Learning & Signal Processing Scientist (Hybrid)
Reports To:
CTO
Our Mission
BlueGreen Water Technologies is leading the charge in helping preserve and promote life on Earth by restoring, safeguarding, and optimizing the health, and safety of waterbodies worldwide – including their wildlife and aquatic biodiversity, ecosystems, and economies – by pioneering and applying proven scientific ingenuity and deep tech solutions.
Our technology suite includes an AI-based software platform with near-real-time remote monitoring of water bodies to enable intelligent, precision-based treatments using our patented nature-based products.
About the Role
We are looking for a skilled and motivated Machine Learning & Signal Processing Scientist to join our team. In this role, you will work on processing and analyzing multi-source environmental and sensor data, including satellites, drones, and in-situ measurements.
Your work will focus on extracting meaningful signals from noisy data, developing robust algorithms, and modeling physical phenomena using advanced statistical and machine learning techniques.
Key Responsibilities
- Process and analyze multi-source sensor data, with a strong focus on noise reduction and signal quality improvement
- Develop and apply time series models to characterize and predict signal behavior
- Design and implement machine learning and deep learning models (e.g., CNNs, RNNs) for spatial and temporal signal analysis
- Build algorithms for detection, classification, and quantification of physical phenomena
- Validate models against real-world data and ensure scientific robustness
- Communicate results clearly through visualizations, reports, and presentations to technical and non-technical stakeholders
- Collaborate closely with cross-functional teams to refine and deploy solutions
Qualifications
- 3+ years of experience in signal processing and machine learning
- Strong expertise in:
- Noise filtering and signal enhancement
- Time series analysis and modeling
- Experience with machine learning and deep learning frameworks
- Familiarity with multi-source sensor data (satellite, drone, or in-situ measurements)
- Experience with remote sensing data, including multispectral and hyperspectral imagery
- Strong programming skills in Python (or equivalent)
- Excellent problem-solving skills and attention to detail
Advantage
- Experience with generative AI or advanced representation learning
- Advantage, use of AI/ML Agents (Claude Code) for enhancing productivity
- Background in geospatial analysis or environmental data
Education
MSc in Physics, Geophysics, Earth Sciences, or a related scientific field (PhD is an advantage)
