Top AI & Machine Learning Jobs

Provides on-site technology leadership at manufacturing sites, translating Smart Manufacturing, AI, data, and digital opportunities into PoCs, PoVs, and MVPs. Builds and validates AI-enabled solutions, evaluates business value and feasibility, addresses governance and deployment barriers, and transitions proven solutions to product teams for scale-up. Partners with stakeholders, coaches site teams, develops reusable engineering patterns, and contributes to product roadmaps.

Builds governed gold-layer data products, semantic models, standardized metrics, Power BI solutions, and applied AI tools. Develops RAG applications, AI agents, embeddings, vector stores, and automated workflows using Microsoft Fabric and Azure AI Foundry. Owns technical delivery from design through production support, including security, governance, testing, monitoring, documentation, and cost management. Collaborates with business stakeholders, mentors peers, and supports adoption of data and AI solutions across manufacturing sites.

Build and own production AI systems, including knowledge pipelines, tool-using agents, automated evaluations, and secure enterprise workflows. Develop backend services, measure AI quality, prevent security risks, and deliver solutions from design through production. Collaborate with product, customer-facing, and engineering teams to solve complex business problems using real-world enterprise data.

Develops and leads production machine learning and image processing solutions for neurovascular OCT and angiographic medical imaging. Responsibilities span algorithm research, prototyping, software architecture, implementation, testing, validation, deployment, and maintenance within regulated medical device systems. The role provides technical mentorship, contributes to ML frameworks and infrastructure, collaborates cross-functionally, performs code reviews, and supports quality, documentation, and compliance initiatives.

Leads Covestro’s North American Digital and AI Centre of Excellence across Canada, the United States, and Mexico. Oversees regional AI and digital transformation programs, KPI performance, stakeholder adoption, team development, project portfolio governance, and budget management. Directs seven data scientists, project managers, analysts, and data engineers while coordinating global initiatives and aligning supply chain technology, analytics, automation, and AI efforts with global strategy.

Lead identification, development, and deployment of AI solutions across manufacturing and business operations. Prototype and implement generative AI, ML, computer vision, LLM-based assistants, and automation. Build Power BI dashboards and data models, integrate AI with ERP/manufacturing systems, and measure outcomes and ROI.

Build and deploy applied AI solutions for R&D, including knowledge systems, generative AI, predictive models, intelligent automation, and decision-support tools. Develop data structures, semantic layers, metadata, retrieval mechanisms, and evaluation practices for reliable AI applications. Collaborate with R&D, IT, Information Security, Legal, and business stakeholders on responsible deployment, security, adoption, and measurable business impact.

Analyzes customer experience and operational data to identify trends and improvement opportunities. Builds Power BI dashboards from complex Excel datasets, automates manual reporting with Power BI and Power Automate, and explores Agentic AI solutions. Presents findings and recommendations to leadership while supporting data quality and data-driven decision-making.

Leads the architecture, development, deployment, and optimization of production-ready AI solutions combining graph databases, knowledge graphs, and LLMs. Acts as a trusted advisor to strategic customers, translating enterprise requirements into scalable Graph+GenAI applications. Responsibilities include stakeholder engagement, solution engineering, cloud deployment, data pipeline design, technical enablement, thought leadership, mentoring, and collaboration with product and marketing teams.

Research and develop AI/ML methods for curating, labeling, typing, and fusing OPIR data. Build out-of-distribution detection pipelines, automated and human-in-the-loop labeling workflows, and data quality and provenance processes. Develop maintainable software, integrate components, test and debug systems, support HEARTH users, and collaborate with government and contractor teams.