Top AI & Machine Learning Jobs

Build and maintain backend services and ML infrastructure to integrate AI models into the Hume platform. Collaborate with research scientists and engineers to develop inference services, evaluation tools, cloud storage and compute solutions, and scalable deployment pipelines for production ML systems.

As an AI Engineer, you will develop and optimize AI systems, focusing on LLM integration, vector databases, and RAG pipelines, collaborating with various teams to ensure cutting-edge performance.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

The research engineer will build and enhance Sapien's AI systems for finance, focusing on agent architecture, data parsing, and performance benchmarking, while developing new intelligent solutions for complex financial workflows.

Provide analytical support in Data Science Division, design analytics solutions, and develop end-to-end analytical lifecycles. Collaborate with diverse teams and present findings to technical and non-technical audiences.

As the first dedicated product hire, you will set product strategy, own the roadmap, and drive features end-to-end. Partner with CEO, design, and engineering, talk to users, and translate customer problems into shipped product. Focus on creating elegant, reliable enterprise AI automation UIs that scale and balance human oversight with autonomous agent execution.

As a Research Engineer specializing in Reinforcement Learning, you'll develop, refine, and evaluate RL techniques and datasets for optimizing language model behaviors in data environments.

As a foundational Software Engineer at Niva, you'll define AI strategy, develop multi-agent AI platforms, and engage with customers to enhance workflows.

The AI Engineer will develop, evaluate, and improve LLM-powered features from prototypes to production, ensuring quality and effectiveness for user deployment.

The role involves leading geophysical simulations and integrating them with AI and ML, defining technical roadmaps, and building a technical team.