Engineering Team Lead

Engineering Team Lead Job Number: 23805 Functional Area: Research - Engineering Department: MIT Quest for Intelligence School Area: Schwarzman College of Computing Employment Type: Full-time (Hybrid) Employment Category: Exempt Visa Sponsorship Available: No Schedule: Email a Friend Save Save Apply Now Job Description ENGINEERING TEAM LEAD, MIT Quest for Intelligence ( -Systems Engineering Team, to lead and supervise a team that is building and maintaining artificial intelligence and machine learning (ML) computational platforms designed to advance Quest missions ( research, compose and benchmark models of natural intelligence, and assess the utility of systems in solving real problems of reasoning and decision-making. Responsibilities include overall planning and execution of technical projects; managing/supervising a team from a range of disciplines; developing complex processing pipelines that evaluate models framed as supervised learning, Bayesian inference, or reinforcement learning problems; designing and leading the integration of Quest systems and software platforms with cloud providers; and other duties as assigned. Job Requirements REQUIRED: M.S. in computer science/ML/related engineering field; seven years' related experience; experience with ML toolkits (e.g., PyTorch, TensorFlow, scikit-learn, MXNet); experience with at least one of the following--computer vision, optimization, time-series forecasting, natural language understanding, reinforcement learning, and/or visualization; experience with software development practices (e.g., git-based version control, CI/CD, etc.); strong project-management, analytical, problem-solving, organizational, decision-making, and written and verbal English communication skills; and ability to lead teams in a dynamic, unstructured environment. PREFERRED: Ph.D.; five years' technical leadership and people management experience; two years' program/project management experience; experience with brain and cognitive research and/or biological data (e.g., experiment design and execution, brain recordings, cognitive measurements); contributions to research communities/efforts, including published papers in ML (e.g., JMLR, NeurIPS, CVPR, ICML, ICCV, ICLR); experience with virtualization and containerization (e.g., Docker), implementing data storage and processing systems (e.g., Hadoop, SQL), and developing and deploying ML applications using a cloud service (e.g., AWS, GCP, Azure); and experience with release management lifecycles, project milestones, managing execution, and high-quality product delivery. Job #23805 3/11/24

Created: 2024-10-19