Own and define the direction of mission-critical solutions by applying best-fit ML algorithms and technologies
Help define and develop MLOps pipelines and containerized solutions to enable secure, robust delivery of models to the enterprise
Work closely with your client to understand their questions and needs
Dig into their data-rich environment to find the pieces of their information puzzle
Develop algorithms, write scripts, and build predictive analytics
Apply ML and deep learning techniques to turn disparate data points into objective answers
Guide clients as they navigate the landscape of ML algorithms, tools, and frameworks
Requirements
1+ years of experience with data science, machine learning engineering, data analytics, or data research
1+ years of experience with an object-oriented language such as Python, C, or Java
Experience with AWS or Azure cloud technologies
Experience building data science and AI or ML solutions that support enterprise operational business and mission use case
Experience with MLOps open-source and Commercial Off the Shelf (COTS) products such as MLFlow, Databricks, Domino, or SageMaker
Experience with projects in NLP, generative AI, or deep learning focus
Ability to design environments that support MLOps pipelines by creating architecture diagrams, process flows, selecting appropriate tooling, and deploying the solution
Ability to work in a team environment and effectively communicate technical concepts to clients, stakeholders, and senior leaders