ABOUT US:

Valkyrie is an applied science firm that builds industry-defining custom AI, ML and Knowledge Engineering solutions. Our interdisciplinary applied science teams support our clients from data normalization all the way through model deployment. Our work can be found across industry from SiriusXM, Activision, Chubb Insurance, and the Department of Defense, to name a few.

The Machine Learning Engineer is the right fit for a motivated engineer that is excited to be part of a growing business, interested in using Machine Learning to solve real-world problems, and is passionate about building ML infrastructure. The right candidate will have strong experience architecting systems for deploying machine learning solutions at scale. In collaboration with our Data Scientists, you will be a part of efforts to improve data and machine learning model reliability and scalability, as well as researching opportunities for data acquisition and new uses for existing data. You will leverage your knowledge of large-scale processing systems to transform data into actionable insights. Our clients come to us when their internal teams can’t figure out a solution. We look to our Machine Learning Engineers to bring both the technical capabilities as well as creative problem solving.
Senior Machine Learning Engineer Qualifications

We encourage candidates to apply even if they don’t have 100% of the below qualifications. We believe in a holistic approach when evaluating talent for our team and post new roles often, so even if this role isn’t quite right, we want to meet you!

• Bachelor’s or master’s degree in Computer Science, Software Engineering, or a related technical field
• 5+ years of professional backend Python development (potentially including NumPy, SciPy, Pandas, Polars, NetworkX & scikit-learn)
• Solid understanding of Python deployment best practices, including dependency management, virtual environments, containerization, etc.
• 2+ years of SQL experience and extensive data processing skills
• 3+ years of cloud experience (AWS, Google Cloud or Azure)
• 2+ years of model deployment experience using TensorFlow Serving, TorchServe, ect
• Robust knowledge of continuous integration and continuous deployment (CI/CD) practices and the ability to set up and manage automated deployment pipelines.
• Ability to develop the transport layer using RESTful API (Flask, Django, or hug)
• 2+ years of strong experience in architecting, constructing, installing, testing, and maintaining highly scalable data management systems
• Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines
• Strong experience in effective collaboration and technical problem solving within multidisciplinary teams
• Experience working with the US Government is a plus
• Experience in large enterprise corporations (like to have)
• Graph Database experience (like to have)
• Experience managing other Engineers (like to have)