Top Tech Jobs & Startup Jobs in Chicago, IL

Design, build, and ship native Android features in Kotlin for BJAK's AI Neobank app. Integrate backend APIs, improve performance, reduce crashes, collaborate with product/design, use analytics to iterate, and add on-device AI where it improves UX.

Build and ship Android and/or iOS features for BJAK's AI Neobank app. Implement insurance, payments, claims and financial flows, integrate APIs, handle edge cases, improve performance and reliability, and support fast product launches and experiments with product and design teams.

Build and ship native iOS features for onboarding, accounts, cards, payments, transfers, rewards and AI-assisted journeys. Improve performance, reliability and UX; integrate APIs and authentication; collaborate with product, design, backend and AI teams; own app quality and production issue debugging.

Build and ship Android and/or iOS features for BJAK's AI Neobank app. Own end-to-end mobile experiences—from product problem through releases—working with backend, design, product and AI teams. Improve app quality using analytics, crash reports, and user feedback, and raise standards for UX, reliability and performance.

Build and ship native Android features for onboarding, accounts, cards, payments, transfers, rewards and AI-assisted journeys. Turn complex financial flows into simple mobile experiences, own app quality (performance, crashes, loading states), integrate APIs and secure authentication, and iterate using production feedback and analytics while collaborating with product, design, backend and AI engineers.

Integrate security into software delivery and infrastructure workflows across AWS and GCP. Build scanning into CI/CD pipelines, maintain security guardrails, secure containerized workloads, implement least-privilege access and secrets management, and support compliance with SC TRM and BNM RMiT. Improve monitoring, vulnerability reporting, incident readiness, and secure delivery practices while collaborating with platform and engineering teams using multiple programming languages.

Lead production-grade ML systems: build data pipelines, training and evaluation workflows, and scalable GPU inference. Fine-tune and adapt large models (LoRA, QLoRA, SFT, DPO, distillation), optimize deployments for latency/cost/reliability, and collaborate with product and engineering to ship robust, observable model-driven features.

Leads the end-to-end execution layer for machine learning, including data pipelines, large-model training and fine-tuning, evaluation, inference, deployment, monitoring, and reliability. Designs scalable GPU-based systems, optimizes performance and cost, partners with research and application engineering, and translates model capabilities into measurable production improvements. Also provides technical leadership, judgment, and support for high-impact ML delivery.

Lead the end-to-end ML execution: build and operate data pipelines, training and evaluation systems, and scalable inference. Fine-tune and optimize large models (LoRA/QLoRA/SFT/DPO/distillation), ensure GPU efficiency, monitor production quality, collaborate with product and application engineering, and rapidly ship reliable, safe ML solutions that translate research into production.

Design, build, and operate large-scale ML systems across data, training, evaluation, inference, and deployment. Lead GPU-optimized training and inference pipelines, ensure reliability, performance, safety, and seamless integration into products. Own production deployments, monitoring, and cross-functional best practices to drive measurable model improvements and efficient research-to-production cycles.