Physical AI Engineering Consultant - Manager - Consulting - Open Location

About the role

The opportunity involves contributing to the delivery of innovative AI solutions, working with a diverse team to design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. The role requires heavy client interaction in a fast-paced environment and the opportunity to develop your own career path.

Responsibilities

• Research, build, and implement scalable artificial intelligence systems that learn and make predictions tailored to business requirements across various environments, including cloud and on-premises.
• Enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes.
• Monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions.
• Lead workstream delivery and ensure effective management of processes and projects.
• Manage professional employees and supervise teams to deliver complex technical initiatives, with accountability for performance and results.
• Engage actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
• Identify opportunities for additional services and manage engagement economics.

Requirements

To qualify for the role, you must have:

• A Bachelor’s degree required (4-year degree). Focused on Business or Economics, Technology Entrepreneurship, Computer Science, Engineering, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning.
• Minimum of 5+ 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, analysing, 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 modelling 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.
• Experience with machine learning algorithms and data architecture design.
• A strong understanding of and/or interest in Agentic AI/Generative AI.
• Knowledge of sustainability practices in technology.
• Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
• Willingness to travel to meet client obligations.
• Deep Learning expertise.
• Knowledge in Image Processing and Analysis.
• Skills in Speech and Audio Processing and Analysis.
• Ability to scale models effectively.
• Strong relationship-building skills.
• Demonstrated client trust and value.
• Effective communication skills with impact.
• Digital fluency and emotional agility.
• Experience in hybrid collaboration.
• Commercial acumen and negotiation skills.
• Proven ability to lead teams and manage change.

Qualifications

To qualify for the role, you must have:

• A Bachelor’s degree required (4-year degree). Focused on Business or Economics, Technology Entrepreneurship, Computer Science, Engineering, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning.
• Minimum of 5+ 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, analysing, 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 modelling 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.
• Experience with machine learning algorithms and data architecture design.
• A strong understanding of and/or interest in Agentic AI/Generative AI.
• Knowledge of sustainability practices in technology.
• Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
• Willingness to travel to meet client obligations.
• Deep Learning expertise.
• Knowledge in Image Processing and Analysis.
• Skills in Speech and Audio Processing and Analysis.
• Ability to scale models effectively.
• Strong relationship-building skills.
• Demonstrated client trust and value.
• Effective communication skills with impact.
• Digital fluency and emotional agility.
• Experience in hybrid collaboration.
• Commercial acumen and negotiation skills.
• Proven ability to lead teams and manage change.