Top Aerospace Jobs in Boston, MA

This role connects customers with engineering, addressing their critical issues and managing the solution process.

The Manufacturing Engineer Co-Op will own parts of the manufacturing process, create documentation, optimize processes, and collaborate with engineers to build hardware while ensuring quality standards.

As a Senior Technical Recruiter, you'll manage sourcing and recruiting for technical roles, collaborating closely with business leaders and ensuring a positive candidate experience, driving initiatives for diversity hiring and implementing effective recruiting strategies.

Develop and maintain web applications on cloud infrastructure, collaborate with teams to containerize apps, implement UIs, and write backend APIs while using Agile and DevSecOps practices.

The Modeling and Simulation Engineer conducts survivability assessments and engagement simulations for high-speed weapon systems, develops vehicle performance models, and utilizes MATLAB and Python for tool development.

The Director of Business Development is responsible for pursuing and capturing opportunities for USAF and USSF contracts, developing strategic plans, and engaging with stakeholders to grow the business.

As a Senior Loads and Dynamics Analysis Engineer, you will focus on load development, perform vehicle dynamics analysis, and validate models while mentoring peers in a fast-paced aerospace environment.

Design, develop, and maintain embedded software for avionics, focusing on low-level development, high-integrity software, and integration testing.

The Enterprise Account Executive will focus on selling digital media solutions to Fortune 1000 clients, crafting strategies, managing leads, and driving sales while traveling frequently.

The Sales Engineer role involves guiding integration of advanced wireless networking solutions for unmanned systems, addressing technical challenges, and ensuring successful deployments while maintaining CRM documentation and customer relations.

Lead a team of ML and DevOps engineers to build infrastructure for the ML ecosystem, including tools for experimentation and deployment. Manage a distributed team while enhancing capabilities in ML system operation and analytics production.