Top Hybrid Machine Learning Engineer Jobs

Build and scale Astronomers context layer for data: design retrieval and semantic search systems, experiment with LLMs and embeddings, turn research into product features, and influence architecture for AI-driven data tools used across organizations.

Embed with clinical and operations teams to identify high-impact problems and build production AI systems. Design and deploy LLM/RAG-driven tools, data pipelines, APIs, models, and user-facing applications using messy clinical and claims data. Iterate quickly based on real-world feedback and operational needs.

The Machine Learning Engineer will propose technical initiatives, lead design discussions, translate challenges into plans, and uphold engineering standards.

Research and build efficient ML systems for large-scale LLMs and agentic RL: design algorithms and system techniques, prototype in training/inference stacks, run large-scale experiments, and translate findings into production or publications.

Develop and maintain a full-stack platform for computational chemists, focusing on drug discovery through machine learning and data infrastructure. Collaborate with interdisciplinary teams to enhance software tools for visualizing molecules and managing workflows.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

The role involves developing advanced machine learning algorithms, solving complex optimization problems using reinforcement learning techniques, and leading technical projects while optimizing solutions for operational efficiency.

Develop, iterate, and deploy machine learning models and agent systems for investment decision-making. Design experiments, build reproducible feature-generation and evaluation workflows, and work with large-scale financial and alternative datasets to identify predictive signals and improve production performance.

Develop AI/ML models for 3D simulation and geology prediction, refine data pipelines, and integrate deep learning tech with product backend.

Build and own Supio's agentic platform end-to-end in TypeScript: production LLM/AI features, agent runtime and prompt/tool architecture, voice/transcription and document workflows, core full-stack customer application, and monitoring/evaluation tooling. Influence architecture and lead greenfield product development with autonomy.