Are you in search for a Machine Learning Engineer that will help accelerate Energy & Infrastructure to new heights? You’re in the right place. Storm4 has a vast network of Machine Learning Engineer candidates who act as a bridge between data scientists. We work with disruptive Energy & Infrastructure companies, connecting them with the most proficient Machine Learning Engineers.
These skilled professionals are leaders in researching, building and designing ML systems that generate responsive algorithms, all with the goal of creating a better, more green future.
An integral member of any data science team, the Machine Learning Engineer will work as a translator between other data scientists, data analysts, data engineers and data architects . Data sets and their verification are second nature, possessing the skill to blend traditional with modern that can help Energy & Infrastructure innovators excel at what they do.
Key ML Engineer Responsibilities include:
- Understand, research, design and develop Machine Learning systems, models and algorithms
- Assess the quality of data sets and data set selection before performing data collection and data modeling
- Perform statistical analysis of data sets to improve models and run machine learning tests, assessing the issues and isolating them in order to improve ML
- Train and re-train ML systems and algorithms, extending machine learning libraries, developing systems according to client requests
- Analyze the results of use cases of ML models and rank them, visualizing data for in-depth insights
Energy & Infrastructure leaders are looking for experienced ML professionals who can understand and create complex ML systems that will skyrocket their businesses.
Storm 4 are proud to connect the best Machine Learning Engineers with the biggest Energy & Infrastructure names in the industry to accelerate the transition to a more sustainable tomorrow.