Top Remote Machine Learning Jobs in Indianapolis, IN

You will lead and mentor engineers while driving the development of solutions for autonomous vehicles using Machine Learning and software engineering principles.

This role involves training AI models in Energy and Power by providing feedback on outputs, problem-solving, and identifying biases in the AI's knowledge base.

As an AI Tutor, you will teach, evaluate, and red-team AI models in data science principles, focusing on statistical modeling, machine learning, and data ethics.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

Lead and scale a distributed Data Engineering and ML organization: design cloud-native data platforms and pipelines, drive ML strategy and integration, mentor global teams, define engineering best practices, and support presales and client engagements for data/ML solutions.

Manage a team of data scientists and analytics engineers to innovate Netflix's core product experience, driving measurement and insights across the TV and interactive discovery domains.

Participate in a 14-month paid apprenticeship while completing Flatiron School's part-time Data Science bootcamp. Contribute to host company software projects, write clean testable code, support feature development, debugging, QA, and documentation, collaborate in sprint workflows, and receive mentorship while building production-ready portfolio work.

Lead Reliability & Observability initiatives, collaborate with engineering and product teams, ensure robust operations of Airbnb's platform, and drive AI projects.

As a Senior Machine Learning Platform Engineer, you'll architect a scalable ML platform, collaborating with teams to ensure compliance, optimize performance, and guide best practices in ML workflows.

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.

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.

Lead QA for AI/ML features: design and execute test plans, build Python automation to validate LLM outputs, guardrails, and data pipelines; perform regression, security/privacy validation, and analyze logs/metrics to ensure reliability.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

Design and maintain ETL pipelines and graph data models to ingest security telemetry into an AWS Neptune knowledge graph, enable ML-driven threat detection, optimize query performance, ensure data quality and compliance, and document workflows.

Lead architecture and engineering for production-grade ML in healthcare: design MLOps CI/CD, scalable low-latency inference for LLMs and classical models, build reliable data pipelines for FHIR/HL7/DICOM, manage cloud IaC and observability, ensure HIPAA/HITRUST compliance, and mentor engineering teams to operationalize agentic AI workflows.

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

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.

Lead the development of first-party measurement solutions, integrate with third-party partners, and ensure high-quality analytics outputs within the ads ecosystem.

The Senior AI Engineer will develop AI solutions for incident management, collaborate cross-functionally, and enhance observability tools through iteration and ownership.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

The ML Platform Engineer will develop and scale ML infrastructure, automate workflows, and collaborate with data scientists to deploy models efficiently in production.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

Develop and optimize machine learning models for financial and operational workflows at Netflix, ensuring model reliability and integration with studio applications.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.