Responsibilities

The Principal Engineer, ML Engineering will lead ML engineering activities for the Shell Energy Platform 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 Shell Energy Platform, and will work across Shell’s global power business, suite of portfolio companies, and enterprise Centers of Excellence to deliver outsized value. Responsibilities include:

Lead ML engineering efforts for Shell Energy Platform

  • 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.
  • Serve as the Shell Energy Platform’s evangelist on best practice ML engineering principles, techniques, tools, and processes. Engage on and inform enterprise-level ML engineering standards, techniques, principles, tools and processes across Shell.
  • Serve as technical architect for designing capabilities that accelerate development speed, value creation, and asset reusability for data scientists across the globe.
  • Guide team delivery and increase throughput on development of ML engineering capabilities and features, as well as commercial project delivery.

Guide and develop a high-performing ML engineering team

  • Team – oversee and develop the emerging Shell Energy Platform ML engineering team.
  • Culture – develop and nurture an empathetic team culture based on respect, collaboration, equal opportunity, diversity, and recognition of strong contributions.
  • Collaboration – Work closely and align principles, tools and techniques with strategy, product management, software engineering, architecture, solution delivery, and commercial teams across Shell Energy Platform and Shell.
  • Process – Embrace best practices in ML engineering, product management, product development, engineering, and user support to deliver outstanding team results.
  • Professional development – support motivating, developing and retaining talent, maintaining a deep talent bench and developing team capabilities needed to succeed.
  • Recruiting – support proactive recruitment of exceptional talent, maintaining a rich pipeline of talent to quickly bring onto the team.

Contribute significantly to Data Science, Data Science Infrastructure, Optimization and MLOps

  • Data Science – support development of Energy Platform’s data science capabilities, including design of frameworks, techniques and tools leveraged across our user base.
  • Data Science infrastructure – support design and delivery of cloud, data and compute infrastructure for data science, ML engineering, optimization, orchestration and ML Ops.
  • Optimization – support design and delivery of optimization capabilities, including design of frameworks, techniques and tools leveraged across our user base.
  • MLOps – support MLOps activities that underpin our delivery and support efforts.

Contribute as senior technical leader of Shell Energy Platform

  • Serve as a technical senior leader of the Shell Energy Platform team, providing expertise, support, and leadership across the team.
  • Support team strategy, culture, planning, productivity and advocacy activities.

REQUIREMENTS:

  • At least 10 years of experience that informs machine learning engineering capabilities in complex energy software solutions with a globally distributed user base.
  • Advanced technical degree strongly preferred (e.g. PhD in computer science, engineering, data science, etc.) or equivalent experience in relevant field.
  • Demonstrated technical expertise and leadership across data science, data engineering, software engineering, orchestration, optimization and infrastructure domains.
  • Demonstrated technical expertise in theory and application of machine learning and artificial intelligence techniques and orchestrations, with preference to application in the energy domain.
  • Development competency in distributed systems, streaming data and functional programming.
  • Development competency across a breadth of languages, frameworks and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Scala, Akka, Reactive Streams, Kafka, etc.
  • 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