AI Engineer – Industrial

This is a fully remote position, open to applicants in New York.

📋 Description

• Create effective AI, machine learning, and optimization solutions that assist technical and operational teams in making complex industrial data more comprehensible, accessible, and actionable.

• Implement advanced AI models, including large language models, foundation models, and multimodal techniques, to develop dependable tools for searching, analyzing, discovering knowledge, and supporting decision-making.

• Construct AI-enabled applications that integrate models, data pipelines, prompts, agents, evaluations, optimization logic, and user feedback into solutions that are effective, transparent, and sustainable.

• Design and leverage knowledge graphs, ontologies, and structured domain knowledge to link process data, experimental data, documents, terminology, assets, materials, and business context.

• Collaborate with domain experts to convert scientific, engineering, process control, and operational inquiries into data products, model workflows, optimization strategies, and user-friendly analytics experiences.

• Develop robust pipelines capable of handling both structured and unstructured data.

• Assist in model validation, monitoring, documentation, governance, and ongoing enhancement to ensure that deployed solutions are reliable in real-world industrial settings.

• Work together with data science, engineering, digital technology, operations, and business teams to deliver solutions that generate measurable value and are designed for ease of adoption.

⛳️ Requirements

• Master’s or PhD degree in Chemical Engineering, Biochemical Engineering, Bioinformatics, Process Control, Computer Science, Data Science, or Applied Mathematics.

• Proven industrial experience with a successful history of delivering measurable business impact and driving outcomes in production or operational settings.

• Hands-on experience with Python and modern machine learning workflows, covering data preparation, modeling, validation, deployment, and monitoring.

• Experience in developing end-to-end AI or machine learning applications.

• Practical knowledge of the capabilities and limitations of advanced models.

• Experience with both structured and unstructured data.

• Familiarity with techniques such as mathematical optimization, process control, forecasting, anomaly detection, recommendation systems, natural language interfaces, classification, deep learning, or predictive analytics.

• Understanding of software engineering principles including version control, testing, application programming interfaces, containers, continuous integration and delivery, and maintainable code design.

• Strong communication skills to engage effectively with both technical and non-technical audiences.

🏝️ Benefits

• Medical

• Dental

• Vision

• 401k

• Vacation

• Holidays

• Paid parental leave (maternity and paternity)

• Annual bonus plan