Sr AI Engineer- Physical AI

Eliassen Group; Omaha (NE); Hybrid; USD 160,000 - 180,000; Full time

Job summary

Eliassen Group is seeking a Senior AI Engineer to lead the development and operationalization of Physical AI systems across stores and supply chains. The role spans robotics, computer vision, ML, and data platforms, translating signals from vision, sensors, IoT, and robotics into scalable, production-grade AI systems.

This full-time position offers a competitive salary and comprehensive benefits. Hybrid work in Charlotte, NC or Seattle, WA with W2 employment.

Qualifications

• Experience building production data pipelines and streaming architectures.
• AI/ML model development and production deployment with MLOps.
• Generative AI and agentic AI exposure with system and solution architecture skills.
• Dashboarding and communication to executive stakeholders.
• Experience with GPU/CPU infrastructure and performance optimization.
• Cloud experience with GCP preferred; AWS or Azure acceptable; hybrid on-prem.
• Edge computing and IoT concepts for real-time inference.
• Experience in digital twins, robotics, Physical AI, supply chain, or warehouse operations.
• Familiarity with CI/CD, SQL/NoSQL databases, Hadoop, Druid, Trino, BigQuery, Vertex AI.
• Knowledge of Kafka and cloud AI platforms.

Responsibilities

• Design and deploy ML and deep learning models for robotics and AI applications.
• Optimize models for real-time edge and scalable environments with GPU/CPU efficiency.
• Integrate perception, planning, and decision-making across AI platforms.
• Build scalable data pipelines and streaming architectures for CV, IoT, robotics, and multimodal data.
• Develop reusable datasets, feature pipelines, and ensure data quality and observability.
• Design and maintain AI platform tools, frameworks, and ML lifecycle infrastructure.
• Implement CI/CD, deployment, monitoring, automation, and MLOps practices.
• Define KPIs, evaluation frameworks, and model performance metrics with experimentation.
• Partner with data science, robotics, CV, platform, and business teams to deliver scalable solutions.
• Translate business requirements into technical AI capabilities and align platform innovation with goals.
• Mentor engineers and promote MLOps best practices.

Skills

Data engineering

ETL pipelines

MLOps

Generative AI

Agentic AI

Edge computing

Cloud platforms

CI/CD

GPU/CPU optimization

Education

Bachelor’s degree in STEM or related field

Master’s degree preferred

Tools

BigQuery

Vertex AI

Kafka

Hadoop

Druid

Trino

Job description

Description

Hybrid 3/2 in either Charlotte, NC or Seattle, WA

Our client is seeking a Senior AI Engineer to lead the development and operationalization of Physical AI systems across stores and supply chain. The role spans robotics, computer vision, machine learning, and data platforms, translating signals from vision, sensors, IoT, and robotics into scalable, production-grade AI systems. The work includes digital twins, agentic AI, and edge deployments to improve operational efficiency, inventory movement, routing, and decision-making.

Description

Hybrid 3/2 in either Charlotte, NC or Seattle, WA

Our client is seeking a Senior AI Engineer to lead the development and operationalization of Physical AI systems across stores and supply chain. The role spans robotics, computer vision, machine learning, and data platforms, translating signals from vision, sensors, IoT, and robotics into scalable, production-grade AI systems. The work includes digital twins, agentic AI, and edge deployments to improve operational efficiency, inventory movement, routing, and decision-making.

This is a full-time, permanent opportunity, offering a competitive salary and comprehensive benefits package. Qualified applicants must be willing and able to work on a w2 basis.

Salary: $160,000 - $180,000/ yr. w2

Job Number #: JN -072026-107939

Responsibilities

• Design and deploy ML and deep learning models for robotics, computer vision, and Physical AI applications.
• Optimize models for real-time, edge, and scalable AI environments with GPU and CPU efficiency.
• Integrate perception, planning, and decision-making systems across AI platforms.
• Build scalable data pipelines and streaming architectures for computer vision, IoT, robotics, and multimodal data.
• Develop reusable datasets, feature engineering pipelines, and ensure data quality and observability.
• Design and maintain AI platform tools, frameworks, and infrastructure for the ML lifecycle.
• Implement CI/CD, deployment, monitoring, automation, and MLOps practices.
• Define KPIs, evaluation frameworks, and model performance metrics with experimentation and A/B testing.
• Partner with data science, robotics, CV, platform, and business teams to deliver scalable solutions.
• Translate business requirements into technical AI capabilities and align platform innovation with goals.
• Mentor engineers and promote engineering and MLOps best practices.

Experience Requirements

• Data engineering and ETL with experience building production data pipelines and streaming architectures.
• AI/ML model development and production deployment with MLOps understanding.
• Generative AI and agentic AI exposure with system and solution architecture skills.
• Dashboarding and visualization with strong communication to executive stakeholders.
• Experience with GPU and CPU infrastructure and performance optimization.
• Cloud experience with GCP preferred, AWS or Azure acceptable, and hybrid on-prem environments.
• Edge computing and IoT concepts for real-time or near real-time inference.
• Preferred experience in digital twins, robotics, Physical AI, supply chain, or warehouse operations.
• Familiarity with CI/CD, SQL and NoSQL databases, Hadoop ecosystem, Druid, Trino, BigQuery, and Vertex AI.
• Knowledge of Kafka, cloud AI platforms, and robotics or computer vision.

Education

• Bachelor’s degree in science, technology, engineering, math, or related field, or equivalent experience.
• Master’s degree in a quantitative or engineering field preferred.