Physical AI Engineering Consultant - Senior - Consulting - Open Location

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.

Responsibilities

• Contribute significantly to the delivery of innovative AI solutions.
• Work with a wide variety of clients to deliver the latest data science and big data technologies.
• Design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape.
• Guide clients through the complexities of modern robotics, digital twin applications, and software engineering.
• Provide technical leadership and perform development tasks to ensure robust engineering and maintenance of physical AI solutions that meet ongoing business needs of our clients.
• Collaborate with a talented team of data and analytics professionals to enhance data pipelines and storage for optimal data accuracy and cleanliness.
• Maintain and optimize learning processes to improve high-performance models.

Requirements

To qualify for the role, you must have:

• 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.
• Experience 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.
• 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 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 foundation in mathematics, statistics, and operations research.
• Experience with machine learning algorithms and data architecture design.
• Knowledge of natural language processing and image processing techniques.
• Understanding of continuous integration and deployment methodologies.
• Experience in scaling models for various applications.
• Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
• Willingness to travel to meet client obligations.

Qualifications

To qualify for the role, you must have:

• A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them.
• 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.
• Experience 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.
• Experience with industry standards and regulations related to robotics and AI, ensuring that solutions meet safety and compliance requirements.
• Experience in 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.
• Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
• Experience fine-tuning Generative AI models.

Skills and Attributes for Success

• Ability to navigate complex challenges and deliver impactful solutions.
• 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 analytical and decision-making skills to guide project direction.
• Technical guidance and sharing knowledge with team members with diverse skills and backgrounds.
• Focus on delivering quality client services, focusing on more complex, judgmental, and/or specialized issues surrounding emerging technology.
• Technical capabilities and professional knowledge.
• Learning about EY and its service lines and actively assessing and presenting ways to apply knowledge and services.
• Strong foundation in mathematics, statistics, and operations research.
• Experience with machine learning algorithms and data architecture design.
• Experience 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.
• Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
• Willingness to travel to meet client obligations.

Benefits

No specific benefits mentioned in the job posting.

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

No specific schedule mentioned in the job posting.