Software Developer

Qualifications & SkillsMINIMUM REQUIRED EDUCATION AND EXPERIENCE: Bachelor’s Degree in Computer Science, Software Engineering, Computer Engineering, Web Development, Human-Computer Interaction (HCI) Data Science, or Electrical Engineering requiredMinimum of 3 years of full stack software development experience required.Expertise in AWS, Azure, or GCP, as well as CI/CD pipelines and containerization software tools.There may be travel required twice per year.This role may interact with confidential information and/or issues, discretion and judgment are required.Must be able to present a portfolio of past projects completed. PREFERRED EDUCATION AND EXPERIENCE:-       Software Architecture – Ability to design scalable,maintainable, and efficient system architectures.-       Cloud & DevOps – Experience with AWS, Azure, or GCP, as well as CI/CD pipelines and containerization (Docker, Kubernetes).-       Database Management – Proficiency in SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Firebase) databases.-       API Development & Integration – Experience with RESTful and GraphQL APIs, third-party service integrations.-       Security Best Practices – Implementing authentication,authorization, and data protection measures.-       Performance Optimization – Enhancing website speed, database efficiency, and server performance.-       Project & Team Management Skills-       Technical Leadership – Guiding engineers through challenges,making architectural decisions, and fostering best practices.-       Agile & Scrum Methodologies – Experience managing sprints, standups, and backlog grooming.‍About MIT FutureTech MIT FutureTech is an interdisciplinary group of economists, computer scientists, and engineers who study the foundations and economic implications of progress in computing and Artificial Intelligence. Economic and social change is underpinned by advances in computing: for instance, improvements in the miniaturization of integrated circuits, the discovery and refinement of algorithms, and the development and diffusion of better software systems and processes. We aim to identify and understand the trends in computing that create opportunities or risks and help leaders in computing, scientific funding bodies, and government to respond appropriately. Our research therefore helps to answer important questions including: Will AI progress accelerate or decline – and should it? What are the implications for economic growth and for the labor markets? What are the bottlenecks to growth from AI, and how can they be solved? What are the risks from AI, and how can we mitigate them? To support our research, we run seminars and conferences to better connect the field of computer scientists, economists, and innovation scholars to build a thriving global research community. To disseminate it, we advise governments, nonprofits and industry, including via National Academies panels on transformational technologies and scientific reliability, the Council on Competitiveness’ National Commission on Innovation and Competitiveness Frontiers, and the National Science Foundation’s National Network for Critical Technology Assessment. Our work has been funded by Open Philanthropy, the National Science Foundation, Microsoft, Accenture, IBM, the MIT-Air Force AI accelerator, and the MIT Lincoln Laboratory. Some of our recent outputs:  The AI Risk Repository: A Comprehensive Meta-Review, Database, and Taxonomy of Risks from Artificial Intelligence Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision? How industry is dominating AI research   The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not)  A workshop on AI scaling and its implications for AI development, automation, and more  The Great Inflection? A Debate About AI and Explosive Growth   There’s plenty of room at the Top: What will drive computer performance after Moore’s law?   Deep Learning's Diminishing Returns: The Cost of Improvement is Becoming Unsustainable  America’s lead in advanced computing is almost gone  The Decline of Computers as a General Purpose Technology: Why Deep Learning and the End of Moore’s Law are Fragmenting Computing  How Fast Do Algorithms Improve?  Some recent articles about our research: Techcrunch: MIT researchers release a repository of AI risks CNN: AI and the labor market: MIT study findings TIME: AI job replacement fears and the MIT study Boston Globe: AI's impact on jobs according to MIT You will be working with Dr. Neil Thompson, the Director of MIT FutureTech. Prior to starting FutureTech, Dr. Thompson was a professor of Innovation and Strategy at the MIT Sloan School of Management. His PhD is in Business & Public Policy from Berkeley. He also holds Master’s degrees in: Computer Science (Berkeley), Economics (London School of Economics), and Statistics (Berkeley). Prior to joining academia, Dr. Thompson was a management consultant with Bain & Company, and worked for the Canadian Government and the United Nations.How to applyPlease use this form to register interest in this role or to submit a general expression of interest.Selected candidates will be first interviewed via Zoom. We are recruiting on a rolling basis and may close applications early if we find a suitable candidate, so please apply as soon as possible to maximize your chances.** To comply with regulations by the American with Disabilities Act (ADA), the principal duties in position descriptions must be essential to the job. To identify essential functions, focus on the purpose and the result of the duties rather than the manner in which they are performed. The following definition applies: a job function is essential if removal of that function would fundamentally change the job.