AI Research & Innovation Team Lead

AI Research & Innovation Team Lead

Herzliya, HA, IL

Company Overview

Imagine Everything. Build the Future with Hexion.

At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress—developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future.

This is where bold thinkers, problem-solvers, and innovators come together to shape what’s next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward.

We don’t follow the status quo—we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger.

We invest in innovation, sustainability, and continuous development—equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.

Your Future Starts Here.

If you’re ready to push limits, reimagine what’s possible, and create the extraordinary, Hexion is where you belong.

Anything is possible when you imagine everything.

Position Overview

We are looking for a hands-on R&I Team Lead to build and drive our next-generation AI capabilities across anomaly detection, explainable AI (XAI), agent-based systems, and state modeling.

This is not a coordination role. You will lead from the front: shaping research directions, writing code, validating ideas in production environments, and turning ambiguity into working systems.

You will manage a small, high-impact team in Herzliya while working closely with platform, product, and domain experts to ensure research translates into real-world value.

Key Responsibilities

• Lead applied research end-to-end: From idea to production: problem framing, experimentation, modeling, evaluation, and deployment.
• Be hands-on: Design and implement ML/DL/LLM-based solutions yourself. Set the technical bar by example.
• Define and execute R&I roadmap: Focus areas include anomaly detection, state estimation, hybrid modeling, and explainable AI (XAI), including causal inference and counterfactual reasoning.
• Bridge research and product: Translate open-ended questions into structured experiments and production-ready components.
• Build and mentor a strong team: Grow a multidisciplinary team (data scientists, analysts, AI engineers) with high ownership.
• Drive technical excellence: Establish best practices for experimentation, validation, and reproducibility.
• Collaborate across the organization: Work closely with platform teams and domain experts to ensure alignment and impact.
• Coordinate with external scientific advisors: Work effectively with domain consultants (e.g. physicists, probabilistic modeling experts) to integrate their insights into the team’s research agenda.
• Communicate clearly and effectively: Present complex ideas to both technical and non-technical stakeholders. This role sits at the intersection of research, engineering, and business.

Minimum Qualifications

• 10+ years experience
• 5+ years of hands-on experience in Machine Learning / Deep Learning / Applied AI
• Proven experience leading technical projects or small teams
• Strong coding skills in Python and modern ML/DL frameworks (PyTorch / TensorFlow)
• Experience with real-world, messy data (time-series, sensor data, industrial systems is a big plus)
• Solid understanding of experimentation, model evaluation, and statistical reasoning
• Experience taking models from research to production
• Strong system thinking. You don’t just build models, you build solutions

Preferred Qualifications

• Background in industrial, sensor-based, or time-series prediction problems.

• Familiarity with anomaly detection and root cause analysis.

• Comfort working in fast-paced environments with evolving data and priorities