Top Remote Senior Level Machine Learning Engineer Jobs in Philadelphia, PA

Sift Healthcare seeks a Senior AI Engineer to enhance ML and AI infrastructure, improve predictive models for healthcare payments, and collaborate with cross-functional teams, requiring 5+ years in an AI role and advanced degree.

Manage and mentor a team of machine learning and data engineers, overseeing ML model development, data pipelines, and collaborating with product teams on technical requirements.

As a Machine Learning Engineer, you'll design, build, and maintain models to detect security threats, ensuring model efficiency and aligning initiatives with business goals.

As a Senior Machine Learning Engineer, you will design and maintain ML systems for content recommendations, search, and spam detection, while augmenting user experience and system performance.

Lead the Performance ML team at MNTN, driving strategy and deployment of predictive models for ad technology, while managing, mentoring, and scaling engineering teams.

Design, build, and deploy end-to-end production ML systems for audience targeting, lookalike generation, and propensity scoring. Own ML lifecycle from experimentation to production monitoring, leverage distributed/cloud platforms, implement vector similarity and embedding systems, engineer scalable features, and collaborate with engineering and product teams to ensure model quality and operational reliability.

The Data & CVML Manager leads the development of autonomy for vehicles, focusing on data and ML processes from collection to deployment, while managing a team and ensuring technical performance aligned with safety requirements.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.