Top Hardware Engineer Jobs in Chicago, IL

The Junior Backend Developer will develop scalable APIs, create tools for media processing and content scheduling, and troubleshoot technical issues. This role focuses on building product functionality to engage users and support the team's operational needs.

The Junior Application Developer will support software product development by participating in full lifecycle projects, developing cloud-hosted web frontends and APIs, and collaborating with cross-functional teams. Responsibilities include coding, issue resolution, and effective communication with clients and team members in an Agile environment.

As Tech Lead for Personalization, you will define and drive the personalization roadmap, leading the design of large-scale recommender systems. You'll mentor ML scientists, collaborate with cross-functional teams, and advocate for innovative solutions leveraging Generative AI.

The Product Engineer II role involves providing technical support and consultation for customers in the industrial automation sector, assisting with product development, and creating marketing collateral. Responsibilities include customer interaction, product inspections, and internal training, requiring expertise in engineering and technical sales within the automation field.

As a Backend/API Engineer at Stripe, you'll design, build, test, and deploy code to improve customer experience for various payment processing initiatives and risk management systems. You'll work on projects across different teams to enhance Stripe's financial infrastructure.

The Sr Solutions Engineer at Contrast Security provides technical leadership throughout the sales process. Responsibilities include technical ownership of sales opportunities, solution demonstration, requirements gathering, and educating clients on application security. The role requires understanding customers' business drivers and mapping them to Contrast's solutions.

The MLOps Engineer will be responsible for training, deploying, and monitoring machine learning models using AWS technologies. They will collaborate with Data Engineers and Data Scientists to develop pipelines and build testing frameworks, leveraging tools like Apache Airflow and Docker. They should have deep knowledge of machine learning frameworks and AWS services for effective model evaluation and implementation.