Job Description

Position Purpose
The Research Software Engineer II (RSEII), Scientific and High Performance Computing at Dartmouth leads the development and management of complex software and data science projects. This role collaborates extensively with Principal Investigators, researchers, students, and external stakeholders to provide robust, secure, and scalable software solutions that meet the evolving needs of Dartmouth’s research community. Skilled in managing rapid developments, the RSEII excels in multitasking and project management. The RSEII focuses on scientific and high-performance computing (both CPU and GPU) to support machine learning and generative AI initiatives. Leveraging emerging technologies, this role tackles complex research challenges and enhances processes. Additionally, the RSEII ensures that AI developments are ethical, sustainable, and aligned with project goals.

Description
Join Our Team as a Research Software Engineer II at Dartmouth!

Are you passionate about pushing the boundaries of scientific and high-performance computing? Dartmouth is looking for a dynamic Research Software Engineer II (RSEII) to lead and innovate in complex software and data science projects.

About the Role:
As an RSEII, you will be at the forefront of developing and managing cutting-edge software solutions that drive Dartmouth’s research initiatives. Collaborating with Principal Investigators, researchers, and students, you will ensure robust, scalable, and secure software solutions. Your expertise in both CPU and GPU high-performance computing will support advanced machine learning and AI projects, solving complex research challenges and enhancing processes.

What You’ll Do:

Lead Projects: Manage large-scale research software projects, ensuring they meet research goals and are scalable for future needs.
Innovate: Implement and optimize high-performance computing solutions, staying current with AI advancements to enhance project outcomes.
Collaborate: Act as a key liaison, ensuring clear communication and alignment between software engineering teams and research stakeholders.
Mentor and Train: Guide junior engineers, develop training programs, and stay updated with the latest trends in software engineering and research computing.

Your Skills and Expertise:

Bachelor’s degree in Computer Science, Engineering, or related field.
At least 3 years of experience in software engineering within an academic or research environment.
Proficiency in Python and AI frameworks like TensorFlow and PyTorch.
Strong understanding of machine learning, data processing, and AI.
Experience with CPU and GPU-based high-performance computing and cloud platforms (AWS, Azure, Google Cloud).

Why Dartmouth?

Impactful Work: Contribute to groundbreaking research and innovative projects.
Collaborative Environment: Work with a diverse and interdisciplinary team of experts.
Professional Growth: Continuous learning and professional development opportunities.

Join Us:
Be a part of a team that is driving innovation in scientific and high-performance computing. Apply now to lead the future of research software engineering at Dartmouth!
Required Qualifications - Education and Yrs Exp Bachelors or equivalent combination of education and experience
Required Qualifications - Skills, Knowledge and Abilities
Bachelor’s degree in Computer Science, Engineering, or a related field.
At least 3 years of experience in software engineering within an academic or research environment.
Strong proficiency in Python and AI frameworks (TensorFlow, PyTorch).
Demonstrated knowledge of generative models (GANs, VAEs) and natural language processing (NLP).
Experience in source code optimization and troubleshooting.
Strong understanding and hands-on experience with machine learning, data processing, and artificial intelligence.
Experience with CPU and GPU-based high-performance computing (HPC), parallel (MPI), and distributed computing.
Experience with cloud platforms (AWS, Azure, Google Cloud) and AI deployment.
Familiarity with key research and scientific programming languages (Matlab, R, SAS, SPSS, STATA) and web frameworks (JavaScript).
Experience leading or contributing to open-source projects.
Familiarity with data security and privacy best practices.
Experience working with diverse and interdisciplinary research teams.
Knowledge of emerging trends and technologies in research software engineering.
Demonstrated commitment to continuous learning and professional development.
Preferred Qualifications
Advanced degree (Master’s or Ph.D.) in Computer Science, Engineering, Data Science, or a related field and publication track record.
More than 5 years in research software development, with a portfolio of complex, multi-disciplinary projects.
Certification in project management (PMP, Agile/Scrum Master).
Advanced proficiency with cloud computing solutions and containerization tools (Docker, Kubernetes).
Significant contributions to open-source projects, showcasing collaborative and community-focused software development.
Experience with ethical AI practices in AI models.
Hands-on experience using large foundation models (e.g., LLMs) and associated tool chains and APIs to build applications, tools, and workflows.