Applied AI/ML Scientist for Autonomous Lab & Process Design

Riven Systems; New York (NY); Hybrid; USD 180,000 - 230,000; Full time

Job summary

Riven Systems in the United States is seeking a Machine Learning Scientist to shape multi-scale modeling by combining ML with rigorous physical modeling. You will collaborate with experts in thermodynamics, hydrometallurgy, process modeling, and autonomous experimentation to steer design decisions.

The role focuses on learned components of thermodynamic/process models, active learning, Bayesian optimization, and surrogate-assisted design, with emphasis on agentic LLM systems and uncertainty

Qualifications

• PhD or equivalent industry experience in a quantitative field.
• Strong background in probabilistic modeling under limited data.
• Experience building with ML agents and large software systems.

Responsibilities

• Build learned components of thermodynamic and process models.
• Own design of autonomous lab experiments via active learning and Bayesian optimization.
• Develop optimization methods for flowsheet design at scale.
• Create agentic systems for LLM-based design and revision of chemical processes.
• Design evaluations to verify agent correctness and quantify uncertainty.

Skills

Bayesian methods

Gaussian processes

Optimization

LLM agents

Interdisciplinary communication

Large software systems

Education

Ph.D. in machine learning or related field

Tools

JAX

PyTorch

Python

Job description

Riven Systems in the United States is seeking a Machine Learning Scientist to shape multi-scale modeling by combining ML with rigorous physical modeling. You will collaborate with experts in thermodynamics, hydrometallurgy, process modeling, and autonomous experimentation to steer design decisions.

The role focuses on learned components of thermodynamic/process models, active learning, Bayesian optimization, and surrogate-assisted design, with emphasis on agentic LLM systems and uncertainty