Emerson Power & Water Solutions is looking for a Machine Learning Engineer to join their team and drive innovation, improve processes, and solve complex issues within their Ovation™ distributed control system (DCS) platform. The goal is to develop AI-driven solutions that enhance plant reliability and satisfy customer demands in critical industries.
Requirements
- Extensive knowledge and expertise in machine learning and its foundations
- Apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning.
Responsibilities
- Be part of a distributed team developing AI, driving innovation, improving processes, and solving complex issues.
- Design and implement algorithms that enable systems to learn from data and make predictions or decisions without explicit programming.
- Develop models, fine-tune algorithms, and deploy scalable machine learning solutions that enable us to deliver exceptional solutions that satisfy customer demands.
- Apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning.
- Provide direction to support data-driven decision-making and automation, and participate in support activities for existing products.
- Balance a strong understanding of customer needs and financial/time constraints with real-world objectives, through research, governance, model development, machine learning, and AI system deployment.
- Work with marketing and project teams to define AI application opportunities in control system applications
Other
- A Bachelor’s degree in Engineering, Computer Science, Technology, or similar technical fields + 5 years of related experience; or Master's degree + 3 years of related experience; or a PhD without experience
- Must have effective communication skills and leadership capabilities
- Willingness and ability to travel occasionally (up to 5%)
- Legal Authorization to work in the United States – sponsorship will not be provided for this position
- You experiment with a wide range of existing technologies while applying new and emerging options that can enhance organizational outcomes.
