Responsibilities:
61 Design and implement a predictive monitoring platform using ML models for anomaly detection, failure
prediction, and optimization.
61 Integrate data from UFE, Opcenter MES, and Teamcenter into a unified operational AI system.
61 Define alerting rules, incident workflows, and automated remediation actions in collaboration with IT/OT
stakeholders.
61 Develop dashboards and KPI visualizations for traceability and operations insights.
61 Design and fine-tune GenAI models (LLMs) to transcribe, summarize, and extract insights from daily
huddle conversations.
61 Enable natural language search and interactive visualizations of trends, recurring issues, and action items.
61 Work closely with shop floor teams to refine system usability, impact, and adoption.
61 Expand platform capabilities with prescriptive analytics, root cause analysis, and self-healing workflows.
61 Ensure AI deployments align with cybersecurity, privacy, and compliance standards.
Qualifications
61 Bachelor’s or Master’s degree in Computer Science, Data Science, Industrial Engineering, or related field.
61 5+ years of experience in AI/ML systems, ideally within manufacturing, IIoT, or smart operations domains.
61 Proficient in Python, with experience using TensorFlow, PyTorch, or similar deep learning frameworks.
61 Experience working with GenAI and LLMs (e.g., OpenAI, Anthropic, Mistral) and building or fine-tuning
ML pipelines.
61 Familiarity with cloud platforms such as Azure, AWS, or hybrid/on-prem environments.
61 Hands-on with data visualization tools (e.g., Power BI, Grafana) and data collection agents (e.g.,
Prometheus, Telegraf).
61 Experience with CI/CD tools such as:
o Azure DevOps, GitHub Actions, GitLab CI, Jenkins, ArgoCD, Tekton, or CircleCI
61 Exposure to DevOps, MLOps, or AIOps automation frameworks and practices.
61 Familiarity with containerization and orchestration tools: Docker, Kubernetes (EKS/AKS/GKE).
61 Nice to have: Experience integrating with MES (Opcenter), PLM (Teamcenter), or other enterprise
platforms in manufacturing.
Soft Skills & Personal Attributes
61 Strong logical reasoning and analytical thinking for solving complex technical and operational problems.
61 Excellent collaboration and communication skills for working with diverse teams and stakeholders.
61 Self-motivated with outstanding time management and prioritization abilities.
61 Passionate about innovation, continuous improvement, and building scalable, high-impact AI solutions.
61 Committed to ethical AI development, with a clear understanding of security, data governance, and
compliance best practices.