ML and Agentic Systems Engineer

Details

NVIDIA's Cosmos team is building multimodal AI, simulation, world models, and agentic systems that can reason about, build, evaluate, and improve AI systems. This role focuses on creating the meta-layer of modern machine learning through agents, tooling, pipelines, and feedback loops that make model development faster, smarter, and increasingly automated.

Responsibilities

• Design and implement agentic workflows across the ML lifecycle, including data generation and curation, evaluation, debugging, training orchestration, and iteration.
• Build AI-native systems in which models and agents interact with codebases, tools, experiments, and environments to improve developer and researcher productivity.
• Create self-improving loops where agents generate data, surface failures, evaluate outputs, and drive better decisions.
• Own and evolve large-scale Python and PyTorch codebases, turning fast-moving ideas into robust, modular, reusable software.
• Design and scale evaluation platforms combining automated metrics, human feedback, and agent-driven analysis.
• Build and maintain multimodal ML pipelines spanning data processing, experimentation, benchmarking, and deployment.
• Integrate open-source and internal components into unified systems for rapid experimentation and reliable iteration.
• Improve engineering practices in testing, reproducibility, packaging, code health, and maintainability.

Requirements

• Significant experience building machine learning systems and software platforms, not only models.
• Expert-level Python skills, with strong judgment around modularity, abstraction boundaries, and long-term code health.
• Deep familiarity with PyTorch, including debugging, adapting, and extending model behavior within larger software systems.
• Experience building pipelines, evaluation systems, developer tooling, or workflow automation for machine learning at meaningful scale.
• Strong software engineering fundamentals, including system design, testing, packaging, debugging, and collaborative codebase evolution.
• Strong agency in LLM-based systems, such as tool use, planning, multi-step workflows, code agents, or automation over data and experiments.
• Ability to operate in fast-moving environments where ambiguous ideas must be turned into useful systems quickly.
• BS, MS, or equivalent experience in Computer Science, Engineering, or a related field.
• 12 or more years of relevant software development experience.

Preferred Qualifications

• Experience building agent-based systems for coding, evaluation, data generation, triage, experimentation, or orchestration.
• Contributions to impactful open-source machine learning, Python, or developer tooling projects.
• Background with context compression and agent memory techniques.
• Familiarity with agent safety and agent identity, including authentication, authorization, and IAM.
• Strong software craftsmanship applied effectively in research-adjacent environments.

Compensation and Benefits

The base salary range is $224,000–$356,500 USD for Level 5 and $272,000–$431,250 USD for Level 6. Base salary is determined by location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.

Applications will be accepted at least until June 26, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.