Physical AI Engineering Consultant - Senior - Consulting - Open Location

EY · Oklahoma City, OK · 3 wk ago

On-siteEngineering$106k–$195k/yrFull-time

About the role

Join EY and help to build a better working world. As a Senior AI Native Engineer, you will be at the forefront of revolutionizing how businesses leverage artificial intelligence. Your role will involve researching, building, and implementing scalable AI systems that learn and make predictions tailored to diverse business environments, whether in the cloud or on-premises. You will enhance data pipelines to ensure data integrity and optimize learning processes, all while collaborating with a talented team of data and analytics professionals.

Responsibilities

Researching and implementing scalable AI systems that meet business requirements.
Enhancing data pipelines and storage for optimal data accuracy and cleanliness.
Monitoring and optimizing learning processes to improve high-performance models.
Guiding clients through the complexities of modern robotics, digital twin applications, and software engineering.
Providing technical leadership and performing development tasks to ensure robust engineering and maintenance of physical AI solutions that meet ongoing business needs of our clients.
This position may have travel requirements as needed to engage with external clients regularly.

Requirements

A Bachelor’s degree required (4-year degree).
Bachelor's degree and 3-6 years of full-time working experience in Robotics, Digital Twin, and Computer Vision/Deep Learning/Reinforcement Learning.
Proficiency in programming languages such as Python, C++, or Java, with experience in robotics frameworks (e.g., ROS) and simulation environments.
Experience designing, building, and maintaining robotics systems and digital twin models.
Hands-on experience with NVIDIA Omniverse or similar simulation environments for robotics and digital twin applications.
Understanding of robotic systems, kinematics, dynamics, and control algorithms.
Understanding of various sensors (e.g., LIDAR, cameras) and actuators used in robotic systems.
Familiarity with creating and managing digital twins, including modeling, simulation, and real-time data integration.
Knowledge of machine learning techniques and algorithms, particularly in the context of robotics and automation.
Proficiency using data manipulation and analysis tools (Pandas, NumPy) to derive insights from sensor data and simulations, and experience with popular ML packages such as TensorFlow, PyTorch, or similar libraries.
Extensive experience using DevOps tools like GIT, Azure Devops and Agile tools such as Jira to develop and deploy analytical solutions with multiple features, pipelines, and releases.
A solid understanding of Machine Learning (ML) workflows including ingesting, analyzing, transforming data and evaluating results to make meaningful predictions.
Experience with MLOps methods and platforms such as MLFlow.
Experience with CI/CD practices to automate the testing and deployment of software in Software-in-the-loop (SIL) environments.
Experience designing, building, and maintaining ML models, frameworks, and pipelines.
Experience designing and deploying end-to-end ML workflows on at least one major cloud computing platform.
A strong understanding of data structures, data modeling, and software engineering best practices.
Proficiency using data manipulation tools and libraries such as SQL, Pandas, and Spark.
Clearly communicating findings, recommendations, and opportunities to improve data systems and solutions.
Experience with containerization and scaling models.
Integrating models and feedback from downstream consumption systems - reporting and dashboards, AI driven applications.
Proficiency in deep learning techniques.
A strong foundation in mathematics, statistics, and operations research.
Experience with machine learning algorithms and data architecture design.
Familiarity with cloud computing and technical design optimization.
Knowledge of natural language processing and image processing techniques.
Understanding of continuous integration and deployment methodologies.
Experience in scaling models for various applications.
A strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
Willingness to travel to meet client obligations.

Qualifications

Advanced degree in Robotics, Computer Science, Mechanical/Aerospace Engineering, Electrical Engineering, or other quantitative field; graduate school years can act as a substitute for some of the industry years requirement.
Previous experience in research projects related to robotics, automation, or digital twin technologies (including academic research), with contributions to academic journals or conferences, showcasing research findings and technical expertise.
Experience with computer vision techniques and libraries (e.g., OpenCV) for object detection, tracking, and recognition.
Proficiency in designing and implementing control systems for robotic applications, including PID controllers, state-space control, and adaptive control techniques.
Ability to develop and optimize algorithms for tasks such as path planning, motion planning, and decision-making in robotics.
Experience with Hardware-in-the-loop (HIL) testing techniques to validate the performance of robotic systems in real-time by integrating hardware components with simulation models.
Knowledge of Model-Based Systems Engineering (MBSE) methodologies to support the design, analysis, and verification of complex systems.
Familiarity with industry standards and regulations related to robotics and AI, ensuring that solutions meet safety and compliance requirements.
Experience with testing methodologies, including unit testing, integration testing, and system testing, to ensure the reliability and robustness of physical AI solutions.
Strong understanding of and/or interest in Agentic AI/Generative AI.
Knowledge of sustainability practices in technology.

Skills and attributes for success

Strong analytical and decision-making skills to guide project direction.
Proven experience in project management and tracking deliverable completion.
Ability to build and maintain relationships with clients and team members.
Excellent communication skills to convey complex ideas effectively.
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
Experience fine-tuning Generative AI models.

Benefits

At EY, we offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $106,200 to $194,600. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $127,400 to $221,100. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

Pay

The base salary range for this job in all geographic locations in the US is $106,200 to $194,600. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $127,400 to $221,100. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.

Schedule

We expect most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.