Research Engineer

Tufts University is seeking a highly motivated and skilled Staff Research Engineer to join our dynamic team. This unique role involves working closely with leading professors on funded projects, focusing on the development and maintenance of both software and hardware infrastructure critical to the project's success. If you are passionate about pushing the boundaries of technology and research within the academic sphere, this position offers a remarkable opportunity to contribute to impactful projects while expanding your knowledge and skills in machine learning and AI.

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  Collaborate with project leads to design, develop, and maintain advanced

software and hardware solutions that support research objectives.

• Implement and optimize algorithms on GPUs using Pytorch and other relevant frameworks.
• Engage in language modeling with transformers, particularly focusing on Large Language Models (LLMs), including working with and contributing to

open-source models.

• Maintain and enhance infrastructure supporting the LLM ecosystem, including

vector databases, LangChain, or other orchestration and training frameworks.

• Contribute to the development of Trustworthy and Accountable AI systems

through rigorous research and innovative engineering solutions.

• Work flexibly across different aspects of the project, demonstrating a willingness to learn and adapt to new challenges and tasks outside of the traditional job description.
• Drive fast iterative execution to achieve project milestones and deliverables in a timely and efficient manner.

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  Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• Strong experience with GPU computing and deep learning frameworks,

particularly Pytorch.

• In-depth knowledge of OS internals and the ability to work closely with hardware and software interfaces.
• Extensive experience with language modeling, specifically using transformers

and Large Language Models (LLMs), both prompting and fine-tuning.

• Familiarity with the LLM ecosystem, including vector databases, LangChain, or other orchestration frameworks.
• Proven track record of being results-oriented, with a high degree of flexibility and a bias towards impactful work.
• Excellent problem-solving skills and the ability to work independently or as part of a team.
• Strong desire to contribute to the field of machine learning research, with a

particular interest in Trustworthy and Accountable AI systems.