Sr AI

Sr AI / ML Applications Architect – GE Vernova GE Vernova is accelerating the path to more reliable, affordable, and sustainable energy, while helping our customers power economies and deliver the electricity that is vital to health, safety, security, and improved quality of life. Join us to electrify and decarbonize the world. Summary We are seeking a highly skilled Sr AI / ML Applications Architect to lead the design, development and deployment of advanced machine learning (ML) and generative AI solutions. The role combines deep technical expertise in AI / ML architecture with leadership responsibilities, requiring someone who can drive innovation from concept to production while managing high‑performing project teams. Key Responsibilities Design and architect scalable AI / ML solutions, including generative AI applications, tailored to grid automation and digitalization technologies as well as business efficiency. Ensure optimal performance across edge and cloud deployment environments. Establish architectural standards, best practices and technical guidelines for AI / ML development across the CTO organization in collaboration with GEV AI / ML partners. Build a strong technical foundation with architecture built on modular / microservices, cloud / edge, API‑first, privacy‑by‑design philosophies; infrastructure concepts of containerization, orchestration, auto‑scale capabilities (compute, storage, network) and infra‑as‑code; development concepts of automation (CI / CD, data and MLOps pipelines), code assist and sandboxes for collaboration + experimentation. Ensure the design and development of AI / ML solutions and project deliveries adhere to the defined framework and are scalable, high‑performant, maintainable, accurate and reliable. Drive technical decision‑making for AI / ML solutions and projects including infrastructure requirements and deployment strategies for both edge computing and cloud‑based solutions. Design and deploy on GE GridNode / edge platforms, using container and microservices principles and best practices. Develop and implement strategies for optimizing performance of models in production. Collaborate with cross‑functional teams to integrate AI / ML capabilities into existing platforms and develop new intelligent business efficiency and product line solutions. Stay current with state‑of‑the‑art developments in AI / ML, generative AI and energy systems technology through continuous monitoring of research and industry trends. Evaluate and recommend emerging technologies and methodologies for their potential application to grid automation challenges and business opportunities; design, execute and demo proof‑of‑concepts (PoCs) to validate new AI / ML approaches and assess their feasibility for energy system applications. Translate research insights and emerging technologies into practical solutions that can be integrated into our product lines. Foster a culture of innovation and learning within the team by encouraging experimentation with new technologies and knowledge sharing of industry developments. Lead end‑to‑end project delivery from ideation through deployment, ensuring projects meet technical requirements, timelines and business objectives. Manage and mentor a small team of AI / ML engineers, data scientists and data engineers, providing technical guidance and career development support. Coordinate cross‑functional project teams, facilitating collaboration between engineering, product, operations and business stakeholders. Collaborate on resource planning and risk mitigation for complex AI / ML projects. Ensure AI / ML solutions meet industry standards, regulatory requirements and cybersecurity protocols for critical energy infrastructure. Required Qualifications PhD or Master’s with a minimum of 5 years equivalent professional experience, in Computer Science, Electrical Engineering, Data Science or related technical field. Minimum of 10 years of hands‑on experience in AI / ML development with 8+ years in architectural roles. Desired Characteristics Proven expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit‑learn, etc.) and generative AI technologies (LLMs, SLMs, diffusion models, GANs). Proven experience in applying AI / ML frameworks / workflows, AI / MLOps and CI / CD using cloud‑native and on‑prem development and deployment in operational technology / industrial automation environments. Experience developing and implementing ML models using cloud MLOps pipelines such as AWS SageMaker, Azure ML, Google Vertex AI, Dataiku Cloud or equivalent. Hands‑on professional experience in developing and testing AI / ML algorithms and demonstrated professional experience with grid / physics models in power system simulation tools, MATLAB / PSCAD; as well as power system analysis software such as PSS / E, Digsilent or equivalent. Experience with DevOps, data pipelines, Azure ML registry, deployment methods (Docker, Kubernetes, etc.). Proven experience designing solutions that include the full AI / ML project lifecycle : data acquisition (real‑times / streaming, batch and response / request), data quality assurance + engineering, model selection and evaluation, tuning, testing, deployment, maintenance and evolution. Experience with Linux virtualized system deployment using VM, Hypervisor (ESXi, KVM, Xen, etc.), Docker and container orchestration tools. Have a combination of GPU experience, Spark and Scala to build and optimize high‑performance, scalable, distributed computing solutions for data‑intensive tasks; familiarity with fault tolerance and high‑availability requirements for mission‑critical applications. Strong background in edge computing, IoT deployments and cloud platforms (AWS, Azure, GCP). Expertise with GraphDB, SQL / NoSQL, MS Access databases. Proficiency in programming languages including Python, C# or C++ as well as scientific programming + simulation tools such as MATLAB or R. Experience with time‑series analysis, signal processing, load forecasting and predictive modeling relevant to energy systems and grid operations. 5+ years of people management experience with demonstrated ability to lead high‑performing technical teams. Proven track record of successfully delivering complex AI / ML projects from conception to deployment. Excellent communication skills with ability to translate complex technical concepts to diverse audiences including leadership and non‑tech stakeholders. Knowledge of regulatory frameworks and cybersecurity requirements for energy sector applications. Track record of applying research insights to solve real‑world business problems and deliver commercial solutions; ability to balance innovation with practical implementation constraints and business requirements. Ability to multi‑task in a fast‑paced multi‑cultural environment. Team player, problem solver, positivity and a can‑do attitude. Excellent communication, presentation, organization and documentation skills. Experience with electrical power systems T&D assets, grid automation, SCADA systems, utility and industrial customers, communications infrastructure, etc. Understanding of industrial IoT, edge computing requirements and real‑time data processing in critical infrastructure environments. Understanding of digital substations, IEC standards & protocols, transmission and distribution automation segment & solutions and virtualization. Root cause analysis skills, troubleshooting and debugging skills using tools such as Wireshark, TCPDump and other Linux and Windows system tools. Experience with reinforcement learning, optimization algorithms or control systems. Additional Information Relocation Assistance Provided Seniority Level Mid‑Senior level Employment Type Full‑time Job Function Engineering and Information Technology Industries Electric Power Generation Location & Salary Markham, Ontario, Canada – Salary range : CA$160,000.00 – CA$180,000.00 (2 weeks ago). Greater Toronto Area, Canada – Salary range : CA$81,000.00 – CA$131,000.00 (1 day ago). J-18808-Ljbffr #J-18808-Ljbffr