Senior AI/ML Applications Architect

Job title: Senior AI/ML Applications Architect

About the Role GE Vernova is seeking an experienced and highly skilled Applications Architect to lead the design, development and deployment of advanced machine learning (ML) and generative AI solutions for grid automation and digitalization. The role combines deep technical AI/ML architecture expertise with leadership responsibilities, driving innovation from concept to production while managing high-performing project teams. You will develop PoCs and ensure deployment of models on edge or cloud-based systems.

What You'll Do

• 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, infrastructure concepts of containerization, orchestration, auto-scale capabilities, and infra-as-code; development concepts of automation (CI/CD, data and MLOps pipelines), code assist and sandboxes for collaboration and experimentation.
• 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; design, execute and demo PoCs to validate new AI/ML approaches.

What We're Looking For

• Minimum of a Bachelor's degree in Computer Science, Electrical Engineering, Data Science or related technical field.
• Minimum of 7 years of hands-on experience within software engineering, AI/ML development and/or architectural roles.
• Desired: Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and generative AI technologies (LLMs, SLMs, diffusion models, GANs).
• Experience 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 VertexAI, Dataiku Cloud or equivalent.
• Hands-on experience developing/testing AI/ML algorithms and demonstrated professional experience with grid/physics models in 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).
• Proven ability designing solutions that include the full AI/ML project lifecycle: data acquisition (real-time/streaming, batch and request/response), data quality assurance and engineering, model selection and evaluation, tuning, testing, deployment, maintenance and evolution.
• Strong background in edge computing, IoT deployments and cloud platforms (AWS, Azure, GCP).
• Expertise in GraphDB, SQL/NoSQL, MS Access databases.
• Proficiency in programming languages including Python, C#, or C++ as well as scientific programming and 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.
• Proven track record of delivering complex AI/ML projects from conception to deployment.
• Understanding of industrial IoT, edge computing requirements and real-time data processing in critical infrastructure environments.

For candidates applying to a Canadian-based position, the pay range is between $126,000 and $189,000 CAD. The specific pay offered may be influenced by factors including experience, education, and skill set. Bonus eligibility: discretionary annual bonus.

Compensation & Benefits

• Salary range: CAD 126,000 - 189,000 per year
• Bonus: discretionary annual bonus
• Relocation: not provided