GenAI & ML Engineer — Production AI for Manufacturing

Slate Auto; Washington; Sur place; USD 123 000 - 185 000; Plein temps

Résumé du poste

Slate Automotive is building an AI-native vehicle platform. This role is for an engineer ready to work on real AI/ML problems in production: GenAI features, data pipelines, and AI applied to manufacturing and supply chain operations.

We value hands-on builders who can ship end-to-end solutions, collaborate across Vehicle Engineering, Manufacturing, and Operations, and translate requirements into reliable AI systems with measurable impact.

Qualifications

• Foundational ML knowledge including training, evaluation, and regularization.
• Experience with supervised learning, NLP, computer vision, and time-series modeling.
• Familiarity with LLM APIs and building on top of them.
• Exposure to RAG, embeddings, or retrieval systems in projects or research contexts.

Responsabilités

• Build and ship AI/ML features across the full model lifecycle from data to deployment.
• Contribute to GenAI systems including RAG pipelines and prompts for reliability.
• Write data pipelines, labeling workflows, and evaluation frameworks.
• Address manufacturing, supply chain, and physical operations AI problems.
• Collaborate with Vehicle Engineering, Manufacturing, and Operations to translate requirements into AI systems.

Connaissances

Python

ML fundamentals

NLP

Computer vision

Time-series modeling

LLM APIs

RAG pipelines

Data pipelines

Experimentation

Communication

Formation

Bachelor's degree in CS/Math/Engineering

MS or PhD preferred

Outils

PyTorch

JAX

Hugging Face

pandas

scikit-learn

AWS

GCP

Azure

Git

MLflow

Description du poste

Slate Automotive is building an AI-native vehicle platform. This role is for an engineer ready to work on real AI/ML problems in production: GenAI features, data pipelines, and AI applied to manufacturing and supply chain operations.

We value hands-on builders who can ship end-to-end solutions, collaborate across Vehicle Engineering, Manufacturing, and Operations, and translate requirements into reliable AI systems with measurable impact.