As a Senior Machine Learning Engineer specializing, you will lead the development and implementation of machine learning algorithms and models to enhance our mapping and location-based services. You will be responsible for leveraging machine learning techniques to extract insights, automate processes, and improve the accuracy and relevance of our map data.
Key Responsibilities:
- Algorithm Development: Lead the design, development, and optimization of machine learning algorithms and models for various mapping applications, including data analysis, feature extraction, image processing, and predictive modeling.
- Data Processing and Analysis: Collaborate with data engineers to preprocess, clean, and analyze map data, including satellite imagery, LiDAR data, and point cloud data, to extract relevant features and patterns.
- Model Training and Evaluation: Train, validate, and evaluate machine learning models using large-scale datasets to achieve high accuracy, robustness, and scalability for mapping applications, such as road detection, object recognition, and semantic segmentation.
- Integration and Deployment: Integrate machine learning models into existing mapping systems and workflows, ensuring seamless deployment and interoperability with other software components. Collaborate with software engineers to develop APIs and interfaces for model integration.
- Performance Optimization: Optimize machine learning algorithms and models for performance, efficiency, and scalability, including algorithm parallelization, hardware acceleration, and deployment on cloud platforms.
- Research and Innovation: Stay updated on the latest advancements in machine learning, computer vision, and geospatial technologies, and apply innovative techniques to solve mapping-related challenges and drive continuous improvement.
Qualifications:
- Master's or Ph.D. degree in computer science, machine learning, artificial intelligence, or a related field.
- 5 years of experience in machine learning research and development, with a focus on computer vision, geospatial analysis, or mapping applications.
- Proficiency in machine learning frameworks and libraries, such as TensorFlow, PyTorch, and OpenCV.
- Strong programming skills in Python, C++, or another relevant language, with experience in software development and version control systems.
- Experience with geospatial data processing and analysis tools, such as GDAL, PostGIS, and QGIS.
- Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
- Effective communication and leadership skills, with experience mentoring junior team members and collaborating with cross-functional teams.