Top Remote Machine Learning Jobs in Indianapolis, IN

Lead the development and deployment of machine learning solutions that enhance content discovery on Netflix, partnering with engineering and creative teams.

Design and maintain scalable ML models for logistics. Own end-to-end projects and collaborate with teams to deliver impactful customer features.

As a Sr. Software Engineer, lead the development of AI-powered systems for Payment Integrity. Collaborate with teams, mentor engineers, and enhance system reliability while processing large-scale unstructured data.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

Develop optimization algorithms for ad personalization, integrate ML model predictions, translate findings for stakeholders, and A/B test features.

As a Principal Data Scientist, you will analyze complex data, create measurement techniques, collaborate with teams, and develop models to enhance Zillow Rentals' marketplace performance.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The Analytics Engineer will lead analytics initiatives for live events at Netflix, where they’ll define metrics, build reporting tools, and drive strategic insights to improve viewer engagement and monetization.

Design and implement a perception system for autonomous vehicles, focusing on data integration from various sensors and ensuring safe operation.

As a Senior Machine Learning Engineer, you'll develop and deploy AI-driven products, build robust ML models, and collaborate with teams to enhance clinical research using advanced AI solutions.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.

Design and implement machine learning models to improve Risk and Fraud detection systems. Lead technical strategy and partner with operations to address rapidly evolving challenges.