AWS ML Cloud Engineer

Industry: Energy
Company size: 1-10
Not disclosed

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Job description

A fast-growing US-based company that uses powerful AI technology to bring the best data to life, enabling businesses in the energy sector to dig through and aggregate a large volume of information, is looking for an AWS ML Cloud Engineer. The developer will be in charge of defining and implementing an effective strategy for building a best-in-class ML protocol. The company's advanced system enables customers to access energy data faster, with greater precision and data integrity. The firm has managed to secure fundings worth more than $1.2 mn so far. This will be a full-time, long-term role that requires a 4+ hours overlap with the CST/PST time zone.


Job Responsibilities:

  • Build, hire and guide the team around data science and ML to deploy models into production
  • Train ML models for extracting and mapping data from PDFs, Excel, and other types of documents into the data model
  • Create, manage and dispatch labeling jobs for improving the ML engine
  • Deploy models into production
  • Work alongside the architecture and engineering teams to design and implement any scalable software services
  • Lead software projects, from start to finish, where the scope is undefined or needs refinement
  • Implement continuous integration/continuous delivery (CI/CD) pipelines where necessary
  • Be responsible for the planning, implementation, and growth of the AWS cloud infrastructure
  • Manage a continuous integration and deployment methodology for server-based technologies

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 5+ years professional experience in software development
  • 5+ years of working experience with Java, Python, and Scala
  • Experience working with RESTful API and general service-oriented architectures
  • Deep understanding and experience in the field of AI, Machine Learning, Deep Learning, and related technologies
  • Experience developing ML models in real-world environments and integrating AI/ML and other AWS services into large-scale production applications
  • Deep understanding of AWS Services such as S3, ECS, EKS, and EMR
  • Experience with AWS services related to AI/ML is highly desirable, particularly Sage Maker, Lex, Rekognition, Textract, and Comprehend
  • Nice to have AWS specialty certification(s) 
  • Desirable to have a data science background and expertise in manipulating/transforming data, model selection, model training, cross-validation, and deployment at scale
  • Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe, and Torch is preferred 
  • Prior domain experience in energy, climate change, or sustainability is a huge plus

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