Machine Learning Engineer at deep tech industrial AI startup

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Machine Learning Engineer – Forward Deployed

Company Description: Deep tech industrial AI startup.

Location: Remote.

Job Description

You will deploy and harden machine learning components in real‑world energy and industrial environments. This role bridges the gap between research and production by operationalising physics‑informed and deep learning models under real‑world constraints. You will ensure the robustness, stability, and explainability of AI systems within complex physical infrastructure and field environments.

Why this role is remarkable

• Deploy cutting‑edge physics‑informed ML models that have a direct impact on global energy and industrial efficiency.
• Work at a well‑funded startup backed by top‑tier VCs, operating at the intersection of deep learning and physical science.
• Lead the transition from lab‑based research to production‑grade deployments in complex, high‑stakes operational environments.

What you will do

• Own and deploy end‑to‑end ML pipelines including data validation, feature extraction, model serving, and performance monitoring.
• Adapt foundation models and algorithms to site‑specific industrial data and infrastructure constraints.
• Collaborate with research teams to translate novel physics‑informed methods into production‑grade, reliable systems.

The ideal candidate

• Proficient in Python and deep learning frameworks like PyTorch or JAX, with experience in Docker and Kubernetes.
• Strong background in applied ML for time series or operational AI within industrial or energy contexts.
• Proven experience productionising ML models with a focus on CI/CD integration, observability, and system reliability.

Seniority level

Entry level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Technology, Information and Internet