Machine Learning Engineer
Description For Machine Learning Engineer
Mariana Minerals is seeking a Machine Learning Engineer to revolutionize the critical minerals supply chain through advanced AI applications. This role combines cutting-edge machine learning with practical industrial applications, focusing on controlling mineral refining facilities and optimizing supply chain operations. The position offers a unique opportunity to work at the intersection of AI and physical infrastructure, developing ML models for chemical operations, implementing reinforcement learning for process control, and leveraging LLMs for engineering applications.
The ideal candidate will collaborate closely with process chemistry teams, software engineers, and subject matter experts in mechanical and chemical engineering. They will be responsible for developing novel data-driven models, implementing control algorithms, and building robust data pipelines. This role requires both technical expertise in machine learning and the ability to bridge the gap between AI theory and practical industrial applications.
Working from the San Francisco headquarters, the successful candidate will be part of a team that's applying advanced technology to solve real-world challenges in the minerals industry. This position offers the opportunity to make a significant impact on critical infrastructure while working with cutting-edge AI technologies. The role requires 2+ years of experience in deploying ML models in production environments and combines the excitement of AI development with the tangible results of physical infrastructure optimization.
This is an ideal opportunity for a machine learning professional who wants to apply their skills to meaningful industrial applications, work with diverse teams, and contribute to the development of critical mineral supply chain infrastructure. The role offers the chance to work on complex challenges while making a real-world impact in an essential industry.
Responsibilities For Machine Learning Engineer
- Develop and deploy ML models to control mineral refining facilities operations
- Train and deploy RL models for mineral processing facilities control
- Build data preprocessing, training, and validation pipelines
- Apply LLMs to parse unstructured data for engineering and construction teams
- Work with process chemistry teams to develop data-driven models
- Use simulator data to pretrain RL control algorithms
- Work with teams to incorporate sensor data to improve model performance
- Implement LLM powered experiences
- Assist with data architecture for data pipelines
Requirements For Machine Learning Engineer
- Strong understanding of ML fundamentals
- Ability to incorporate research ideas into production applications
- 2+ years experience developing and deploying ML models in production settings
- Self-starter mindset
- Ability to bring clarity to high ambiguity situations
- Experience working with subject matter experts in mechanical, chemical, and process engineering
- Ability to work across the entire stack from data pipelines to model inference and monitoring
