Machine Learning Engineer

Pluralsight

4d•$121,600 - $160,000•Hybrid

About The Position

A Machine Learning Engineer helps our learners discover content that is relevant to their interests and goals, providing them with experiences tailored just to their needs, and ensure they are receiving the right communication and assistance with their journey at the right time. They develop robust, scalable production machine learning algorithms and recommendation systems. Who you’re committed to being: You enjoy learning and are open to new ways of doing things. You are not afraid to be yourself, experiment, make mistakes and learn from them, ask questions, or voice your concerns. When communicating you are self-aware, insightful, and proactive.

Requirements

Experience building production machine learning systems services as part of a product development team
Experience in Python, TensorFlow, and proficiency in data structures and database fundamentals
Experience building good code with speed and efficiency and balancing the trade-offs of quality vs speed
Ability to explain machine learning solutions to developers and other team members, regardless of their technical background
Experience working with continuous integration and delivery
Familiarity with cloud platforms and deploying ML models as scalable services
Experience with containerization and orchestration tools such as Docker and Kubernetes
Knowledge of software design patterns and best practices, including RESTful API design
Requires a minimum of 5 years of related or equivalent experience; or 3+ years with an advanced degree

Nice To Haves

Ideal experience in using machine learning in the context of recommendations and/or personalization.
Experience with Node and Typescript preferred

Responsibilities

Work closely with Data Scientists to take prototype algorithms and models and turn them into customer-facing solutions
Build solutions to novel problems in software development, data engineering, and machine learning
Build data pipelines; transform and convert data streams into structures needed for algorithm input
Collaborate with Product Managers and UX Designers to better understand the customer, provide valuable input into functional design and usability
Evaluate the efficiency of user experiences and ML algorithms, determining what data is needed and how to collect it, with an understanding of how these metrics are connected with the desired outcomes