Responsibilities include :
- Lead ML engineering efforts for our client
- Serve as the senior ML engineering expert for a global platform and global commercial operations that rely on best-in-class ML techniques, software engineering and MLOps .
- Development competency in data engineering and storage, including across breadth of tools such as S3, RDS, EFS, No-SQL, graph db, Spark, etc.
- Experience in energy management domain is a plus, with comfort in energy asset optimization, asset control and data flow loops, and wholesale electricity market applications
Our client's organization is leading efforts to design, develop, deliver and maintain a global energy management platform that unlocks value across their company. They aim to enable their efforts to harness the potential in its vast fleet of customers, energy assets, and power trading capabilities to deliver value across the energy industry value chain. The organization is a nimble, cross-functional, deeply technical and passionate group that embodies the speed and agility of a startup while embracing the scale of one of the largest companies in the world. Achieving a balance between agility and global scale provides unique opportunities, and they borrow from best-in-class product development, continuous delivery, and commercialization approaches while adapting them to their unique global scale.
- Manages one or more data engineering projects of moderate complexity.
- Leads or acts as key team member in defining and builds the data pipelines that will enable faster, better, data-informed decision-making within the business.
- Jointly designs and implements a new big data solution which supports high amounts and velocity of data and supports future growth. Identifies latest development, testing and deployment techniques to quickly deploy new releases to eg deploy new data pipelines and add data sources.
- Takes direct reports, when applicable, through Agile Framework and its respective tools.
- Influences stakeholders in adopting analyzes / outcomes.
- Acts proactively to support the business to further professionalize their MI / Analytic reporting platform, using the ESSA approach.
- Opinions valued by business interface.
- Plays a prominent role in project related meetings etc.
- Utilises business partnering in order to gather, analysis and model data and key performance indicators of the highest complexity.
- Working as Data Engineering
- Lead to develop and deploy innovative big data platforms for advanced analytics and data processing.
- Works independently under broad managerial supervision.
Machine Learning (ML) Engineer will lead ML engineering activities for our client and significantly contribute to data science, data engineering, optimization engineering, orchestration engineering and ML Ops efforts. This experienced engineer will grow and optimize this critical technical foundation for our client, and will work across their global power business, suite of portfolio companies, and enterprise Centers of Excellence to deliver outsized value. Apply now