Top AI & Machine Learning Jobs

Develop reinforcement learning systems for autonomous agents by designing high-fidelity 2D/3D simulation environments, reward functions, and policy architectures. Implement and optimize algorithms such as PPO, SAC, and Offline RL for high-dimensional observations. Develop sim-to-real strategies using domain randomization and adaptation, collaborate with ML, annotation, and program management teams, and ensure reliable agent performance and environment parity.

Design and implement software architecture integrating machine learning models with real-time rendering systems. Evaluate customer requirements, determine build-versus-buy approaches, and route specialized needs to deep learning or reinforcement learning teams. Develop language-agnostic wrappers, APIs, and microservices while coordinating technical requirements among customers, leadership, and engineering. Translate product visions into modular, scalable, maintainable software components.

Leads the architecture and deployment of AI-powered agentic workflows and automation across DreamWorks’ animation production pipeline. Designs frameworks, integrates digital content creation tools, manages telemetry, evaluates AI models, and delivers reliable production-ready tools. Partners with artists, engineers, platform teams, and security teams to reduce manual work, establish standards, monitor performance, drive adoption, and measure productivity impact. The role also includes prototyping, documentation, training, and mentoring across technical and creative departments.

Lead development of scalable AI-powered systems, rapidly evaluate frontier AI capabilities, and translate them into measurable business value. Build APIs, web frontends, business logic, data layers, and SQL/NoSQL storage. Deploy and troubleshoot cloud applications, create automated tests, maintain code quality, and integrate foundation models, RAG patterns, and agentic AI. Collaborate across multidisciplinary teams to move prototypes into production and deliver solutions in complex, matrixed environments.

Design, develop, and optimize LLM-powered applications and autonomous agents. Build agentic workflows with LangGraph, implement prompt engineering, integrate and evaluate LLMs, develop observability capabilities, maintain MCP servers, and deploy backend services using AWS-native technologies. Collaborate cross-functionally, participate in Agile ceremonies, conduct peer reviews, and contribute to engineering standards for reliable, scalable AI systems.