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Senior Machine Learning Engineer
1 month ago
At RIGID ROBOTICS, we are on an exciting journey to transform the mining industry. By harnessing the power of precision sensing, IoT, and AI-driven decision-making our vision is to optimize the performance of large mining shovels.
Our innovative solutions not only significantly boost operational efficiency and human safety but also bring substantial environmental benefits, including reduction in greenhouse gas emissions and explosive usage.
Key Responsibilities:- Design, develop, and deploy algorithms and machine learning models for a range of applications, particularly those targeting edge computing platforms.
- Work with various sensor data (position, orientation, etc.) to develop predictive and classification models.
- Build and maintain ETL pipelines to ensure clean, accessible, and structured data for model development.
- Apply deep learning and classical machine learning techniques to solve real-world problems.
- Optimize machine learning models using techniques like quantization, pruning, and knowledge distillation.
- Collaborate with cross-functional teams to understand project goals and data requirements.
- Conduct performance analysis, model validation, and error diagnosis.
- Stay current with industry trends and advancements in machine learning, AI, and sensor data processing.
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
- 6+ years of experience in machine learning, data science, or a related role. Specifically, experience in the commercial phase of ML and AI product is required as a senior staff.
- Excellent problem-solving skills and the ability to work independently or in a team.
- Strong knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
- Proficiency in classical machine learning methods (e.g., SVMs, decision trees, clustering).
- Experience working with IMU, GPS sensor data and other time-series data.
- Experience in ETL pipelines: data extraction, transformation, and loading.
- Hands-on experience with model optimization techniques, including quantization, pruning, and knowledge distillation.
- Proficiency in Python and common ML/AI libraries (NumPy, Scikit-learn, etc.).
- Strong understanding of signal processing, especially for sensor data.
- Experience with model deployment and MLOps best practices.
- Mining and/or Industrial environment experience.
- Experience with edge machine learning (Edge ML) and deploying models to edge devices (e.g., Raspberry Pi, NVIDIA Jetson, mobile devices).
- Experience with IoT or edge computing applications.
- Experience with cloud platforms like AWS, Azure, or GCP
- Competitive salary and benefits package.
- Opportunities for professional growth and development.
- Supportive and collaborative start-up work environment.
- Work at the cutting edge of technology in the challenging environment of the mining industry.
- Contribute to more sustainable and efficient mining operations.
