Sr Full-Stack AI Engineer, IPAI, SMAI

United States Digital Space LLC; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

United States Digital Space LLC is seeking a Sr Full-Stack AI Engineer to design, build, and deploy production‑grade AI applications across global fab and assembly/test plants. You will own AI products end‑to‑end—from data pipelines to web front‑ends and edge deployment—serving fab engineers, operators, and leadership.

You will collaborate with robotics, data science, and operations teams to deliver scalable, observable platforms and 3D digital twin environments that drive decisions and

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related field; equivalent industry experience accepted.
• Experience delivering in complex, cross‑functional environments with data science, robotics, operations, and infrastructure teams.
• 5+ years building and shipping production web or AI applications end to end.
• Excellent Python and modern JavaScript/TypeScript skills; scalable solution design.
• SQL fluency and experience with at least one cloud (AWS, Azure, or GCP).
• Hands-on with Docker + Kubernetes; CI/CD pipeline ownership.
• Experience designing data ingestion and feature pipelines for AI/ML workloads at scale.
• Familiarity with LLMs, GenAI, MLOps/LLMOps, and model safety practices.
• Hands-on with digital twin platforms (Omniverse, Gazebo, Unity Robotics Hub, etc.).
• Bonus: semiconductor manufacturing or regulated high‑reliability environments.

Responsibilities

• Design, architect and build end‑to‑end AI products: data ingestion, feature pipelines, model training/inference, APIs, web UI, and observability.
• Develop responsive front‑ends in React, Angular, or Streamlit, backed by Python/FastAPI, with strong type‑safety and test coverage.
• Architect scalable, modular layers linking real‑time sensor data with dashboards and decision‑support tools.
• Integrate robotics platforms, AMRs, tool automation, and control systems with smart manufacturing apps.
• Create digital twins and 3D representations using Gazebo, Omniverse, or Unity for simulation and validation.
• Deploy containerized services via Docker/Kubernetes; manage GPU‑accelerated inference and CI/CD releases.
• Work with existing Smart Manufacturing systems to feed AI pipelines and 3D twins.
• Ensure responsible AI practices: input validation, redaction, and model risk logging.
• Collaborate across cross‑functional teams to ship production‑grade AI solutions.

Skills

Python

JS/TS

SQL

Cloud platforms

CI/CD

LLMs

MLOps

Education

Bachelor's or Master's in CS/SE/DS

Tools

Docker

Kubernetes

NVIDIA Omniverse

Gazebo

Unity Robotics Hub

Siemens Tecnomatix

Unreal Engine

Job description

Sr Full-Stack AI Engineer, IPAI, SMAI

Join the company at a defining moment in our history. We are seeking a hands‑on, results‑driven Full‑Stack AI Engineer to design, build, and deploy production‑grade AI applications across our worldwide fab and assembly/test plants. Reporting to the Industrial and Physical AI director, you will own AI products end to end – from data pipelines and model training to web/mobile front‑ends, APIs, and on‑prem or edge deployment – shipping the tools that put AI into the hands of fab engineers, operators, and leadership across this global program.

Job Responsibilities

• Design, architect and build end‑to‑end AI products: data ingestion, feature pipelines, model training/inference, APIs, web UI, and observability
• Develop responsive front‑ends in React, Angular, or Streamlit, backed by Python/FastAPI, with strong type‑safety and test coverage
• Architect and maintain scalable, modular application layers that bridge real‑time sensor/robotics data with enterprise‑facing dashboards and decision‑support tools
• Design and develop full‑stack integration of robotics platforms, Autonomous Mobile Robots (AMRs), tool automation, and control systems with smart manufacturing applications and the Micron smart manufacturing ecosystem
• Design and implement digital twin environments — constructing 3D representations of fab layouts, AMR fleets, and tool stations using Gazebo, NVIDIA Omniverse, or Unity Robotics Hub for simulation, path planning validation, and operational rehearsal
• Interface with existing Smart Manufacturing systems to feed structured data into AI pipelines and 3D digital twins
• Integrate LLMs and agentic AI frameworks into production workflows for fab engineers
• Build AI‑assisted robotics orchestration and develop 3D‑aware AI features – enabling models to reason over spatial data (equipment positions, robot trajectories, fab zone maps) for anomaly detection, route optimization, and predictive maintenance
• Containerize services with Docker, deploy via Kubernetes / OpenShift, and automate releases with CI/CD
• Package and deploy robotics software stacks and 3D rendering services as containerized microservices, supporting both edge (fab‑floor) and cloud execution environments
• Manage GPU‑accelerated inference workloads for both AI models and real‑time 3D physics simulation (e.g., NVIDIA Isaac Sim on cloud)
• Optimize performance and cost: caching, batching, GPU utilization, model quantization, and right‑sizing inference for edge or cloud
• Apply Responsible AI practices: input validation, prompt‑injection defense, PII/IP redaction, model risk and audit logging
• Validate 3D simulation scenarios against real‑world operational constraints before deployment to ensure zero‑defect autonomous operation

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field; equivalent industry experience accepted
• Track record of delivering in complex, cross‑functional environments – collaborating across data science, robotics, operations, and infrastructure teams
• 5+ years building and shipping production web or AI applications end to end
• Excellent Python skills and modern JavaScript/TypeScript experience, with experience in designing and architecting solutions to ensure scalability
• SQL fluency
• Hands‑on experience with at least one cloud (AWS, Azure, or GCP) and with Docker + Kubernetes; CI/CD pipeline ownership
• Experience designing data ingestion and feature pipelines for AI/ML workloads at scale
• Working knowledge of LLMs and the GenAI stack: prompt engineering, function/tool calling, RAG, agentic patterns; familiarity with MLOps / LLMOps and model evaluation/safety practices
• Hands‑on with digital twin platforms: NVIDIA Omniverse, Unity Robotics Hub, Gazebo, Siemens Tecnomatix, or Unreal Engine would be an advantage
• Bonus: prior experience in semiconductor manufacturing, 3D modeling, digital twin solution development or any regulated high‑reliability environment

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.