Senior Machine Learning Engineer – Industrial Innovation & Generative AI

• Lead the design, development, and deployment of advanced analytics components within industrial systems, with a focus on Generative AI, LLMs, computer vision, and signal processing.
  
• Build production-ready document intelligence pipelines to extract, validate, and structure data from semi-structured documents (e.g., invoices, statements, forms) using OCR + LLM workflows, including quality checks and exception handling.
  
• Develop LLM-powered “policy/rule reasoning” services that interpret complex eligibility/contract/tariff-like rules and match them against site/customer profiles to recommend optimal options and outcomes.
  
• Design and implement agentic workflows for scalable information discovery and data acquisition (e.g., automating collection of public/partner data sources), including tooling, safety constraints, and evaluation.
  
• Create orchestration, monitoring, and cost controls for GenAI systems (tracing, latency/error monitoring, token usage/cost, standardized logging/alerts) to ensure production reliability.
  
• Own end-to-end delivery: from feasibility studies and prototypes to deployment-ready services (APIs, batch jobs, workflows), collaborating with software engineers, platform/MLOps, and domain experts. 
  
• Establish evaluation methodology for LLM/agent systems (gold datasets, accuracy metrics, regression tests, offline/online evaluation, failure mode analysis) and drive iterative improvement.
  
• Mentor and lead technically, contributing to engineering standards, reusable templates, and knowledge sharing across teams.
  
• Contribute to innovation outputs (internal tech talks, invention disclosures/patents, publications where relevant)
  

Requirements

• Senior Level - Master’s or PhD in Computer Science, Data Science, Mathematics, Engineering, or a related field.
  
• Senior Level - 7+ years building ML/AI systems in industrial, infrastructure, or enterprise settings, including taking solutions from prototype to production.
  
• Senior Level - Strong Python engineering skills and experience with ML/AI libraries and modern software practices (testing, packaging, APIs, CI/CD).
  
• Senior Level - Proven hands-on work with LLMs / Generative AI in applied settings, including prompt design, tool-using agents, and retrieval/grounding patterns (RAG).
  
• Senior Level - Experience building information extraction / document understanding solutions (OCR pipelines, structured outputs, validation, human-in-the-loop flows).
  
• Senior Level - Practical knowledge of workflow orchestration and production pipelines (e.g., Airflow-like orchestration, job scheduling, dependency management).
  
• Senior Level - Strong understanding of observability for AI systems (logging, tracing, evaluation, monitoring, and cost governance for LLM usage).
  
• Senior Level - Comfortable collaborating with stakeholders to translate ambiguous domain problems into measurable ML deliverables and robust services
  
• Senior Level - Experience in utilities / energy / building operations / infrastructure analytics, especially where cost optimization and rules-driven decisions matter. Prior work in time-series/signal processing or industrial monitoring, including anomaly detection and fault diagnostics.
  
• Senior Level - Computer vision experience (industrial or remote sensing), active learning, few-shot adaptation.
  
• Senior Level - Demonstrated innovation track record (patents / invention disclosures / technical publications)