Top Remote Senior Level QA Engineer Jobs in Rochester, NY

The Senior Energy Engineer will manage onboarding of new sites, develop and implement energy management programs, support performance monitoring of energy resources, identify optimization opportunities, and assist business development through proposals and presentations.

The Senior Fullstack Engineer will collaborate with a talented team to design, build and innovate a procurement platform, ensuring high quality throughout the development lifecycle and implementing best practices. The engineer will deliver continuous business impact and communicate effectively with stakeholders.

As a Senior Software Engineer, you will develop and maintain software systems, lead design and coding efforts, ensure security and privacy compliance, solve complex technical issues, and engage in testing and documentation while collaborating with cross-functional teams.

The Solutions Architect will support utility clients by crafting solutions that meet customer goals through a consultative sales process. Responsibilities include gathering technical requirements, defining integrations, advocating for customer needs, and supporting various sales and implementation objectives.

As a Senior Open Source Web Developer, you will design, create, and document high-performing open source solutions using PHP and Javascript. You will lead architectural decisions, collaborate with teams, conduct code reviews, and mentor others while ensuring the development team adheres to best practices and documentations.

As an Ecosystem Technical Solutions Engineer, you will engage in building the Dagger ecosystem through community engagement, partner engineering, and creating technical content. Your role includes educating users, documenting feedback, and developing strategies to enhance Dagger's capabilities while supporting integrations related to CI/CD, AI/ML, and data pipelines.

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.