Job Description

Etteplan is a highly multitalented, collaborative technology service company that solves challenges and drives change collectively — bringing people and technology together with a strategy of Transformation with AI. We help the world's leading industrial companies develop smarter, safer, and more connected products.

We are looking for an embedded AI Architect to drive AI adoption across Industrial Product Solutions business unit. You will be the bridge between cutting-edge AI innovation and real-world embedded product development — from edge inference on microcontrollers to AI-augmented engineering workflows.

Your main responsibilities in this role would be

• Architect end-to-end AI solutions across edge devices, on-premises gateways, and cloud back-ends — covering on-device inference, anomaly detection, predictive maintenance, and computer vision.
• Act as a trusted technical advisor for customers exploring AI integration and support sales teams in communicating AI value and feasibility.
• Define model selection, compression, and deployment strategies for resource-constrained embedded targets.
• Initiate and lead multidisciplinary AI projects from concept to production

Your skills and experience to success in this role

• Solid understanding of AI/ML fundamentals model training, inference optimization, and deployment pipelines.
• Hands-on experience with embedded systems development (bare-metal and RTOS environments) and embedded AI/Edge AI frameworks
• Proficiency in C/C++ for embedded firmware and Python for ML experimentation and MLOps tooling.
• Experience designing cloud-edge hybrid architectures and knowledge of relevant embedded communication protocols.
• Strong communication skills — able to bridge data scientists, hardware engineers, and business stakeholders.
• Strong English fluency required. Finnish fluency is definitely an advantage.

We also value if you have

• Experience with Small Language Models (SLMs) or Generative AI on edge hardware.
• Familiarity with agentic AI workflows, RAG architectures, or computer vision pipelines on embedded targets.
• Knowledge of functional safety standards (IEC 61508, ISO 26262) and cyber security standards (IEC62443 ja ISO/SAE 21434) and their intersection with AI.
• Background in FPGA-based AI acceleration or emerging dedicated inference accelerators.