Top Tech Jobs & Startup Jobs

Manage and own the Integrated Master Schedule (IMS) for products and programs. Develop, maintain, and validate schedules across NPI and factory-buildout workstreams, track performance versus baseline, quantify risks and impacts, and drive cross-functional alignment and accountability. Systematize scheduling standards and automations to scale scheduling processes.

Own and operationalize cost accounting across multi-site manufacturing. Lead GAAP and CAS-compliant rate setting, tighten work order variance reporting, implement costing software, and build SOX 404(b) controls for inventory and costing while partnering with leadership on processes and special projects.

Own and maintain the Integrated Master Schedule (IMS) for programs and products, aligning engineering, supply chain, and operations. Track schedule performance, identify risks, drive mitigation, facilitate cross-functional reviews, and systematize scheduling standards, automations, and reporting to ensure on-time delivery across NPI and factory buildouts.

Lead and grow the Data Platform team that builds ingestion, streaming, warehouse/lakehouse, orchestration, schema governance, quality, lineage, and foundational data models. Own roadmap, reliability SLAs, incident response, architecture tradeoffs, cross-team partnerships, and hiring to scale the platform across factories and operational systems.

Design, develop, and deploy multimodal vision-language models to interpret manufacturing documentation (drawings, CAD, quality docs). Build annotation tooling, active learning loops, and synthetic data strategies. Create evaluation frameworks, collaborate on AI platform roadmaps, and drive production model health and deployment for factory-scale automation.

Lead research, development, and production deployment of object detection and segmentation models for document, layout, and part understanding. Build annotation tooling, active learning loops, synthetic data strategies, and evaluation frameworks, collaborate on ML roadmap, and improve model accuracy to drive manufacturing automation.

Own the ML lifecycle for LLMs applied to manufacturing data: fine-tune and deploy models for document classification, information extraction, table parsing, and multi-page reasoning; build annotation tooling, active learning, and synthetic data pipelines; develop evaluation frameworks; collaborate on AI platform roadmap and optimize model accuracy and production health.

Lead the design, development, and deployment of intelligent automation systems focusing on robotic manipulation and control in manufacturing environments.

The Manufacturing Engineer oversees production support, integrates customer expectations, leads transitions to high-volume manufacturing, and enhances processes with automation and software collaboration.

Design, develop, and commission automated robotic cells for high-precision manufacturing. Collaborate with hardware and software engineers to execute machining strategies.