Are you up to the challenge? At ePlus, we engineer transformative technology solutions for the most visionary companies in the world. This takes imagination, relentless client service, and the tenacity to enable our clients to achieve their visions. Our partnerships with leading-edge technology manufacturers—many of which look to us for their own technology infrastructure needs—keep us immersed across the broad spectrum of the IT ecosystem.
As a Solutions Director (AI/Machine Learning), you will be responsible for setting the strategy and go-to-market plans for current and emerging solutions. You will transform the way we engage with our customers by creating and integrating solution offerings from our OEM partners into ePlus’ Lifecycle Management process. You will collaborate with our national delivery teams to refine, simplify and differentiate our advanced solutions while building go-to-market plans for the introduction of new, emerging technology solutions. This position will offer you the opportunity to work with cross-functional supporting groups, and sales regions, to develop packaged solutions that deliver profitability and sustainable growth for these services and technologies.
From strategy to fulfilment to managed services, our engineering-centric solutions enable our clients to realize what it means for technology to do more.
- Experience with containerization and orchestration (Kubernetes)
- Experience with AI Optimized Infrastructure solutions (GPU/HPC). Knowledge to include CUDA or OpenCL, preferred
- Roll out AI Workloads for scalability and efficiency to include storage, compute, and converged infrastructures
- Experience designing and implementing Apache Open Source (Kafka, Storm, Spark) Frameworks to process end to end data management life cycle for NLP, Machine Log Algorithms, Text Mining algorithms.
- Java Programming at User Interface (UI) level
- Experience with Python, C/C++ and/or R programming in one or more of the major machine learning frameworks: PyTorch, TensorFlow, MXNet, or Caffe.
- Strong oral and written communication skills, including presentation skills (MS Visio, MS PowerPoint).
- Strong problem solving and troubleshooting skills with the ability to exercise mature judgment.
- An advanced degree in the area of specialization
- Experience to Architect, Position, Design, Develop and Deploy enterprise solutions which include components across the Artificial Intelligence spectrum such as Chatbots, Virtual Assistants, Machine Learning, and Cognitive Services (e.g. Vision/Image, Textual/Language processing).
- Perform data studies and data discovery routines for video, voice, weblog, sensor, machine and social media data sources or mash ups of new and existing data sources
- Good understanding of supervised and unsupervised deep/machine learning algorithms, including regression, classification, k-nearest neighbor and random forest.
- Solid understanding of processing pipelines for transforming one or more types of unstructured data (natural language, images, text and/or audio).
- Ability to translate technical features into tangible customer business benefits
- Ability to work collaboratively within a team and cross-functionally within the company.
- Ability to communicate in a clear and concise professional manner, tailored to the appropriate audience; including both verbal and written communications
- Must be able to manage multiple priorities and tasks within a dynamic work environment.
- Some travel, domestic and international, is required
- Define and execute third party solutions in the artificial Intelligence area
- Build and demonstrate third party AI solutions within our lab
- Lead projects working with cross-functional teams to build and demonstrate solutions
- Create technical presentations for internal enablement and customers
- Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
- Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions
- Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements