Heterogenous Software Engineer-Assistant Staff

 

The Embedded and Open Systems Group is a diverse team of talented engineers and scientists developing and prototyping the software and processing solutions for the nation’s security needs of today and tomorrow. Our open and adaptive architectures help the nation’s aircraft, vehicles, vessels, unmanned systems, sensors, communications, ground stations, and bases across the globe rapidly react to evolving needs. Proven expertise in embedded computing, distributed systems and global battle management allows us to optimize the effectiveness and efficiency of data processing, availability, and utility across diverse user communities. Our ultimate success is the fielding of our technologies to meet real-world needs through system analysis, architecture definition, design, prototyping, field testing, and transition to operation.

 

The group is committed to a diverse and inclusive workplace. We understand that a diverse workplace fosters a creative and productive atmosphere and we are dedicated to making sure that every staff member in the group is supported in their work and that every voice is heard. The Laboratory sponsors resource groups and events dedicated to a wide variety of identities.

 

Position Description

We are seeking engineers with the skills and passion to design, prototype, and optimize high-performance software for processors composed of heterogenous computational elements such general-purpose CPUs, GPU accelerators, and more. You will work with algorithm designers and fellow software engineers to realize real-time execution of novel signal, data, and control processing algorithms on distributed, heterogenous systems. Solutions will need to be deployable to multiple tactical environments requiring you to apply your core skills to rapidly adapt and prototype to changing needs. To be successful in this position, you must be versatile, innovative, self-disciplined, and highly collaborative in multi-disciplinary teams spanning MIT Lincoln Laboratory (MIT LL) and the broader Department of Defense (DoD) community.

What you’ll do:

• Design, develop, prototype, evaluate, and optimize real-time software implementations of novel algorithms on heterogenous processing systems.
• Build libraries of core advanced signal and data processing kernels to adaptively meet diverse program needs.
• Research, design, prototype, and mature open architectures/standards for heterogenous processing software and hardware.
• Evaluate commercial offerings to meet our unique technology needs.
• Give technical briefings on your work to your teams, MIT LL community, and sponsors.

 

To be successful in this role you will need:

• A Bachelor’s degree in Computer Science, Electrical Engineering, or related fields.
• Proficiency in C++ software development and implementation for general-purpose CPUs.
• Experience working in a Linux-based environment.
• Experience in software development and implementation for GPU accelerators.
• Experience working in a technical project team(s).
• Experience with industry-standard tools for version control, issue management, and code reviews such as Git and Jira.
• Experience in producing well-documented software and related technical artifacts.
• Effective written and oral communications skills in technical environments.
• Able to obtain and maintain a government (DoD) security clearance
• U.S. Citizenship is required

 

You will stand out if you demonstrate any of the following:

• Experience with Nvidia’s CUDA API.
• Experience in deploying and optimizing software for distributed systems such as multi-core and multi-board processors.
• Experience with adaptive digital signal processing and/or linear algebra.
• Experience with computational acceleration of AI/ML training and inference.
• Experience with radiofrequency systems particularly radar and/or communication systems.
• A willingness to participate in field operations such as system integration and test campaigns.

 

Growth Opportunities

We support a wide variety of mechanisms for staff to continually grow their skills including:

 

• Direct mentorship within the Group and across MIT LL for projects and career guidance.
• Participation in programs across MIT LL to broaden your network internally and externally.
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