Top Tech Jobs & Startup Jobs in Chicago, IL

Lead FP&A activities including annual and rolling forecasts, budgeting, variance analysis, program-level financial reporting, and building scalable models and dashboards. Partner with business leaders, operations, GTM, accounting and legal to translate strategy and customer commitments into financial plans, revenue commitments, and program performance metrics while strengthening FP&A controls and automation in a high-growth environment.

The Director of Product Management for AI Generation Engine will lead product strategy and execution in Finance & Risk Modeling, focusing on innovative AI solutions and close collaboration with financial services clients.

Lead product strategy and development for AI Simulation products, translating scientific needs into product requirements and ensuring market fit.

The Data Engineer will develop and maintain data pipelines, build data models, ensure data quality, and support cross-functional teams while improving internal data platform infrastructure and documentation.

The Staff Technical Product Manager will drive product strategy and definition for AI solutions targeting life sciences, ensuring alignment across teams, validating product market fit, and leading product launch activities.

Lead month-end close and build government cost accounting and compliance infrastructure. Design cost allocation, indirect rates, audit-ready reporting, controls, policies, and support government/DCAA audits while partnering cross-functionally to scale finance operations.

The VP of Operations will architect the AI Simulation business unit, optimize processes, manage resources, and lead strategic initiatives in AI-driven science, overseeing BioSim and ChemSim divisions.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

Join SandboxAQ as a Scientific Software Engineer to develop AI-driven computational chemistry tools and maintain production-quality software, collaborating with experts to enhance drug discovery processes.

The role involves managing the ML lifecycle, developing scalable ML systems, and collaborating on AI-first product solutions focusing on Large Quantitative Models.