Senior AI Engineer: AI for Mechatronics & Robotics

Eigenblue

New York (NY)

On-site

USD 150,000 - 210,000

Full time

14 days+

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Job summary

eigenblue is seeking a Senior AI Engineer to build AI products from the ground up in New York. You will develop AI solutions powering physical R&D automation, working closely with our founding team to shape the future of AI-driven multidisciplinary system design.

The role demands 3–6+ years in AI/ML with LLM deployment experience and strong cloud/MLOps capabilities. You'll design scalable AI systems, build MLOps pipelines on Azure/AWS/GCP, and deploy production APIs with Docker, Kubernetes, and

Qualifications

  • Master's or PhD in Computer Science, Software Engineering, or a related discipline.
  • Hands-on AI/ML development with 3–6+ years of experience.
  • Experience deploying LLMs and building MLOps pipelines on cloud platforms.

Responsibilities

  • Develop and deploy advanced AI solutions (LLM and non-LLM) for physical R&D automation and system design.
  • Design and test approaches for AI reasoning using proprietary ontology and data.
  • Build production-ready MLOps infra with cloud platforms, Docker, Kubernetes, and FastAPI.
  • Collaborate with AI/Data Engineers, Product Managers, and Software Teams to integrate AI features into products.
  • Implement and optimize RAG systems, multi-agent architectures, and fine-tuning pipelines while addressing biases and evaluation metrics.

Skills

LLM deployment
MLOps
CI/CD pipelines
RAG systems & multi-agent
Reinforcement learning / planning

Education

Master's or PhD in Computer Science or Software Engineering

Tools

Docker
Kubernetes
FastAPI
Azure
AWS
GCP

Job description

eigenblue is seeking a Senior AI Engineer to build AI products from the ground up in New York. You will develop AI solutions powering physical R&D automation, working closely with our founding team to shape the future of AI-driven multidisciplinary system design.

The role demands 3–6+ years in AI/ML with LLM deployment experience and strong cloud/MLOps capabilities. You'll design scalable AI systems, build MLOps pipelines on Azure/AWS/GCP, and deploy production APIs with Docker, Kubernetes, and

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