Top Remote Machine Learning Jobs in Indianapolis, IN

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

Drive AI/ML-powered personalized experiences on Pinterest by defining product vision, collaborating across teams, and launching new features to enhance user engagement.

The role leads predictive modeling and machine learning initiatives, mentors team members, and drives innovations in data science for credit risk and operations.

The Director drives the predictive modeling strategy, mentors others, leads initiatives, and advises on data strategy and innovation in credit risk and collections.

As a Machine Learning Engineer, you will design, develop, and deploy machine learning systems, collaborate on AI features, and ensure reliable production performance.

The Principal Machine Learning Engineer will improve diffusion models, conduct research, implement techniques, and collaborate on production-ready systems in AI for fashion.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

The Staff ML Ops Engineer builds and maintains infrastructure for ML applications, ensuring they are robust and production-ready, while collaborating with data scientists and ML engineers.

The Staff Software Engineer, AI/ML will design and develop intelligent agents, integrate them with existing systems, optimize performance, and collaborate with product teams, focusing on innovative AI technologies.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

Develop and implement ML algorithms for bioinformatics, debug models, collaborate with teams, and maintain high-quality Python code.

Lead the ML strategy at The Browser Company, focusing on developing and optimizing ML features for a new browser. Oversee a team of ML engineers and ensure quality in product deployment.

The Senior Applied Scientist will develop and integrate advanced AI/ML models for estate planning, leading projects and collaborating with teams on complex data processes and applications.

Design and implement ML systems for ads targeting, drive technical direction, mentor junior engineers, and collaborate cross-functionally for product development.

The role involves designing and scaling ML infrastructure for LLMs, including building training pipelines and deploying models in cloud and on-prem environments. Collaboration with engineers and managing GPU/TPU workloads is key.

The role involves leading ML/AI solutions, managing technical roadmaps, collaborating with stakeholders, and driving innovation in products and services.

The Senior ML Engineer will design and deploy large-scale ML systems for personalized recommendations, directly impacting user engagement and revenue. Responsibilities include building models serving 100M+ predictions daily and optimizing data processing pipelines.

The role involves building and optimizing large-scale ML systems for personalized recommendations that drive engagement, retention, and revenue, impacting millions of users daily.

The role involves building and optimizing machine learning systems for ad performance, collaborating with teams to enhance targeting and revenue. Responsibilities include developing algorithms, conducting experiments, and improving infrastructure for scalable ad decisioning.

As a Senior ML Engineer, you will develop and optimize ad algorithms to enhance engagement and revenue, collaborate with teams, and implement scalable ML systems.

The Machine Learning Engineer will build and scale ML models, collaborate with cross-functional teams, and improve real-time recommendations for Stitch Fix's clients.

Design and architect AI/ML solutions, build document parsers and classifiers, maintain AI systems, and collaborate with cross-functional teams.

The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.

The role involves sourcing and recruiting senior engineers in AI, ML, and related fields, building talent pipelines, and collaborating with engineering leadership.

Lead the design and implementation of deep learning models for biological data, focusing on model architecture, project leadership, and innovation in machine learning applications in biology.