Machine Learning Engineer

Pluralsight
Remote - USA$122k – $160kPosted 7 April 2026

Job Description

Job Description: 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. What you’ll do: 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 Experience you’ll bring: 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 Ideal experience in using machine learning in the context of recommendations and/or personalization. Experience with Node and Typescript preferred Requirements: Requires a minimum of 5 years of related or equivalent experience; or 3 years with an advanced degree This is a remote role; however, applicants located within 45 miles of our Westlake/Dallas, TX office should expect to work on-site Tuesday through Thursday, with remote flexibility on Mondays and Fridays. This approach enables more effective collaboration, quicker decision-making, and a stronger culture, while still providing flexibility. Why you’ll love working here: We work in a blended environment that supports collaboration, flexibility, and connection across teams. We are mission-driven, shaping the future of tech upskillling and delivering impact that matters. We foster a culture of inclusion and belonging, where everyone can contribute and thrive. We are always learning, creating an environment where you can take on new challenges, expand your skills, and grow with purpose. Benefits include competitive compensation, bonus eligibility, comprehensive medical coverage, unlimited PTO, wellness reimbursement, professional development funds, and more. About us: Pluralsight provides the only learning platform dedicated to accelerating the technology skills and capabilities of today’s tech workforce. Thousands of companies, government organizations and individuals around the world rely on Pluralsight to support critical technology skill development in areas that are crucial to innovation including artificial intelligence, cloud computing, cybersecurity, software development, and machine learning. We offer highly curated content developed by vetted technology experts, industry leading skill assessments, and hands on, immersive learning experiences designed to he ... (truncated, view full listing at source)
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