Adjunct Associate Faculty in Applied Machine Learning I (Fall '26)

The School of Professional Studies at Columbia University is on the lookout for a dedicated data analytics professional to join us as a part-time Adjunct Associate Faculty in our graduate course, Applied Analytics Frameworks & Methods I.In today's data-driven world, vast amounts of information are generated at unprecedented speeds through business transactions, online interactions, social media, and various sensors. This influx provides unique opportunities for predicting outcomes and understanding phenomena across diverse fields, including medicine, business, and space exploration. Our course emphasizes supervised learning techniques that facilitate effective predictions and insights. Students will navigate the data-wrangling process, starting with data exploration and foundational methodologies, before diving into supervised learning techniques such as linear regression, decision trees, and support vector machines. Additionally, students will engage in a predictive analytics competition to apply and integrate their learning.As an Adjunct Associate Faculty member, you will play a pivotal role in supporting the instructional process and providing subject matter expertise. This position is an excellent opportunity to gain experience in graduate-level teaching at Columbia University.Key ResponsibilitiesAttend all scheduled class sessions, assist with instruction, lead breakout sessions, and facilitate discussions.Evaluate and grade student work and assessments as directed by the course Lecturer.Address and respond to student concerns and inquiries.

Columbia University is on the lookout for analytics professionals to join as part-time Adjunct Associate Faculty for an advanced course on Applied Generative AI in Fall 2026. This role offers an incredible opportunity to gain firsthand experience in graduate-level teaching while contributing to the academic community.The Applied Generative AI course introduces students to the fascinating field of generative modeling, a vital aspect of machine learning. Participants will explore theoretical foundations, practical applications, and gain hands-on experience using high-level APIs and open-source foundational models. The curriculum covers essential methodologies for employing, fine-tuning, and programmatically working with cutting-edge Generative AI tools. Students will also delve into the intricacies of low-level model implementations, empowering them to train and understand models based on their data, from foundational principles. Various generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers, will be examined, with applications spanning text, image, audio, and video generation.Key ResponsibilitiesParticipate in all class sessions, assist with instructional duties, lead breakout sessions, and facilitate engaging discussions.Assess and grade student assignments and evaluations as directed by the course Lecturer.Address student inquiries and concerns in a timely and supportive manner.

The Applied Analytics program at Columbia University is excited to invite seasoned data analytics professionals to join our team as a part-time Associate Faculty  for the graduate-level course Applied Deep Learning and AI. This advanced course immerses students in deep learning concepts, integrating essential components from Statistical Machine Learning. Participants will establish a robust foundation in supervised learning alongside various algorithms and methodologies. Key topics include Support Vector Machines, Neural Networks, Convolutional Neural Networks (CNN), word embeddings, attention mechanisms, transformers, encoder-decoder architectures, Generative Adversarial Networks (GAN), and Reinforcement Learning. Practical applications will provide students with insights on preparing, training, testing, and validating models.An Associate Faculty member plays a pivotal role in delivering subject matter expertise and enhancing the instructional experience for course participants. This position offers an exceptional opportunity to gain invaluable exposure to graduate-level teaching within the prestigious environment of Columbia University.Responsibilities:Attend and engage in all on-campus class sessions, assist with instruction, lead breakout discussions, and facilitate student engagement.Evaluate and assess student work as directed by the course Lecturer.Address student inquiries and concerns proactively.Conduct regular office hours for student support.

Join Columbia University as an Adjunct Lecturer in Applied Deep Learning and Artificial Intelligence for the Fall 2026 semester. This role offers a unique opportunity to engage with students and impart knowledge in a rapidly evolving field. As part of our esteemed faculty, you will have the chance to contribute to the academic growth of our students and help shape the future of technology.

Columbia University is seeking experienced analytics professionals to join our faculty as part-time Adjunct Associate Faculty for a graduate-level course titled Analytics for Cybersecurity Management. This role offers a unique opportunity to contribute your subject matter expertise and support the instructional process for aspiring cybersecurity leaders. Engaging in this capacity will provide valuable exposure to the academic environment at Columbia University.This course serves as a comprehensive introduction to foundational cybersecurity principles, including network security, threat detection, and vulnerability management. It emphasizes the transformative impact of emerging technologies such as AI and machine learning on modern defense strategies. Participants will engage with key frameworks and advanced tools through real-world case studies, gaining insights into the role of analytics in effective threat intelligence, incident response, and regulatory compliance.Students will enhance their practical skills through hands-on exercises and interactive assignments, culminating in a project focused on automating vulnerability analysis. They will learn critical tasks such as log parsing, vulnerability classification, dashboard visualization, and AI-driven anomaly detection, while also addressing ethical, legal, and regulatory issues in cybersecurity. By the conclusion of the course, participants will be equipped to design proactive defense measures and adeptly navigate diverse threat landscapes, leveraging AI and analytics to bolster digital security against evolving cyber threats.Key ResponsibilitiesAttend all class sessions, assist with instruction, lead breakout sessions, and facilitate engaging discussions.Evaluate and grade student assignments and assessments as directed by the course Lecturer.Monitor student progress and address any concerns or inquiries in a timely manner.

The School of Professional Studies at Columbia University is actively seeking seasoned industry professionals to join our academic team as part-time Adjunct Associate Faculty for a graduate-level course in Cloud Computing. This position provides a unique opportunity to contribute to the instructional process while gaining valuable experience in graduate-level teaching at Columbia University.The Cloud Computing course is designed to expose analytics students to practical applications and concepts of cloud computing, including infrastructure, administration, and various services and applications. Emphasis will be placed on developing hands-on skills for utilizing cloud services to create distributed and scalable analytics applications.Key ResponsibilitiesParticipate in all class sessions, support instructional delivery, lead breakout sessions, and facilitate engaging discussions.Assess and grade student submissions and evaluations as mandated by the course Lecturer.Address and manage student inquiries and concerns proactively.

Columbia University is seeking skilled analytics professionals to join our faculty as a part-time Adjunct Associate for the graduate-level course Mathematics for AI. As an Adjunct Associate, you will provide essential subject matter expertise and support the instructional process for this course section, gaining valuable exposure to graduate-level teaching at Columbia University.Key Responsibilities:Participate in all class sessions, assist with teaching, and lead breakout sessions to enhance student engagement.Deliver class lectures and facilitate discussions, ensuring a rich learning environment.Assess and grade student assignments and assessments as requested by the course Lecturer.Monitor student inquiries and concerns, providing timely support and guidance.

Columbia University invites accomplished analytics professionals to join as part-time Adjunct Associate Faculty for the graduate-level course on Managing Data. This position offers a unique opportunity to gain firsthand experience in graduate-level teaching while providing critical subject matter expertise. As an Adjunct Associate Faculty member, you will support the instructional process and engage with students in a dynamic learning environment.The Managing Data course equips students with essential skills for effective data management, enabling them to leverage data confidently in collaboration with technology teams. The curriculum addresses the challenges posed by diverse data languages and techniques, offering a comprehensive overview of data technologies, database engines, foundational principles, governance processes, and organizational requirements to ensure data quality.Key ResponsibilitiesAttend all class sessions, assist in instructional activities, lead breakout sessions, and facilitate engaging discussions.Evaluate and grade student assignments and assessments as directed by the course Lecturer.Address student inquiries and concerns promptly and effectively.

Join our team at Columbia University as a part-time Adjunct Associate Faculty for an advanced course on AI User Interfaces for Analytics. This role offers analytics professionals an exceptional opportunity to contribute their expertise while gaining valuable experience in graduate-level education at one of the leading institutions in the world.Key ResponsibilitiesParticipate in all class sessions, assist with instructional delivery, lead breakout discussions, and engage students in meaningful dialogue.Conduct class lectures and oversee instructional activities, ensuring a conducive learning environment.Assess and grade student assignments and assessments as required.

Join the Applied Physics team as a Machine Learning Specialist at our Advanced Propulsion Laboratory in New York! We are looking for a driven and talented individual to engage in pioneering research within dynamic and evolving fields. Key Responsibilities: Investigate and analyze advanced Machine Learning algorithms tailored to specific challenges. Develop, train, and validate algorithms for targeted problem areas. Assist in integrating these algorithms into comprehensive programmatic systems that depend on such technologies. Work collaboratively in a multidisciplinary team environment to achieve research objectives. Engage in both independent and joint research initiatives while collaborating with a diverse range of scientists within and outside the Laboratory. Publish findings in peer-reviewed journals and present at conferences, seminars, and meetings. Travel as necessary to coordinate with collaborators and conduct site visits.

The School of Professional Studies at Columbia University is actively seeking seasoned industry experts to join our faculty as part-time Lecturers for our graduate-level course in Cloud Computing. As primary instructors, Lecturers play a crucial role in shaping the academic environment and fostering a vibrant faculty community.This course serves to immerse analytics students in the essential concepts and practical applications of cloud computing, with a focus on infrastructure management and the deployment of services and applications. The curriculum is designed to equip students with hands-on skills necessary for building distributed and scalable analytics applications using cloud technologies.Key ResponsibilitiesDeliver engaging lectures, facilitate instructional activities, and lead classroom discussions. Commitment to attending all scheduled class sessions.Proactively address student concerns and inquiries to ensure a supportive learning environment.Assess and grade student assignments and evaluations with fairness and transparency.Hold regular office hours for student consultations and guidance.

Columbia University is actively seeking qualified professionals to join our team as part-time Adjunct Associate Faculty for the graduate-level course titled Introduction to Blockchain, Cryptocurrencies & Analytics. This course is designed to impart essential knowledge about blockchain technology and cryptocurrencies to our Master of Science students in Applied Analytics. Topics covered will include cryptographic protocols, hashing, digital signatures, transaction chaining, decentralization through proof of work mining, and smart contracts.The role of an Adjunct Associate Faculty member is pivotal for providing expertise and facilitating the learning process within the course. This position offers an excellent opportunity to gain valuable experience in graduate-level education at Columbia University.

Columbia University is seeking skilled analytics professionals to join us as part-time Adjunct Associate Faculty for a graduate-level course on Artificial Intelligence of Things (AIOT) starting in Fall 2026. This role provides an exceptional opportunity to engage in graduate-level teaching while contributing subject matter expertise and supporting the instructional process.The course aims to equip students with a thorough understanding of IoT technologies and their integration with AI and robotics. Participants will delve into IoT architecture, critical components, and communication protocols, and will gain hands-on experience with IoT platforms, sensors, and data acquisition devices. The curriculum emphasizes practical AIOT applications for real-time decision-making in various sectors, including manufacturing, public safety, smart cities, and healthcare, while also addressing ethical considerations associated with these technologies.Through a combination of conceptual learning and practical assignments, the course features weekly lectures, readings on IoT fundamentals, and biweekly quizzes to evaluate understanding. Students will apply their knowledge through individual assignments and a collaborative term project, ensuring a solid foundation in IoT analytics and AI-driven robotic automation.

At PermitFlow, we are transforming the future of construction across America. As a pioneering applied AI firm, we address one of the most significant information challenges in the construction industry: comprehending what can be built, where, and how. Our innovative AI-driven agents empower the nation’s most rapidly growing construction companies to navigate the complexities of permitting, licensing, inspections, and project closeouts—thereby expediting housing, clean-energy, and infrastructure development nationwide.The construction sector, valued at $1.6 trillion, faces substantial delays, resource wastage, and unrealized opportunities. PermitFlow has successfully provided enhanced speed, accuracy, and visibility to over $20 billion in development projects, aiding contractors in minimizing compliance time, mitigating project risks, and scaling operations with assurance.As the U.S. enters a new capital expenditure supercycle encompassing data centers, factories, housing, and renewable energy, becoming a part of PermitFlow means constructing the AI infrastructure that underpins every construction project and propels the upcoming wave of reindustrialization.We have raised over $90 million, recently completing our Series B funding round, backed by prestigious investors such as Accel, Kleiner Perkins, Initialized, Y Combinator, Felicis, and Altos Ventures, with support from industry leaders at OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber.Our headquarters are located in New York City, offering a hybrid work schedule (3 days in the office per week). Preference will be given to candidates based in NYC or those willing to relocate.

The School of Professional Studies at Columbia University is inviting applications for the role of Adjunct Associate Faculty for a graduate-level course titled Analytics for Business Operations Management, starting in the Fall of 2026. This part-time position offers a unique opportunity to engage in graduate-level teaching while contributing to the academic community at one of the world's leading institutions.This course aims to equip students with analytical techniques to enhance operational decision-making, increase efficiency, and tackle real-world challenges in operations management. Enrolled students will gain hands-on experience in key topics including process analysis, forecasting, queuing theory, simulation, optimization, inventory analysis, project management, supply chain management, and lean operations. By combining lectures with practical coding exercises, the course fosters a comprehensive understanding applicable across various industries.Key Responsibilities:Participate in all class sessions, assist with instruction, and lead breakout discussions.Deliver lectures and facilitate engaging classroom discussions.Assess and grade student assignments as directed by the course Lecturer.Address student inquiries and concerns promptly.

Pinterest’s Advanced Technology Group is looking for a Machine Learning Intern at the master’s level for Fall 2026. This internship centers on visual search and recommendation systems, blending research and engineering in a collaborative environment. Interns may help launch new features for millions of users or take part in academic research projects. Role overview This 12-week paid internship runs from September 21 to December 11, 2026. Work may be remote or hybrid, with office locations available in San Francisco, Palo Alto, Seattle, or New York. Team placement determines whether the role is remote or hybrid. What you will do Build and launch new user features using internal datasets and machine learning techniques. Conduct research focused on visual understanding and recommendation systems. Work closely with engineering teams and take part in external collaborations or mentoring. Contribute to features that may reach millions of users or support research for academic publication. Locations San Francisco, CA Palo Alto, CA Seattle, WA New York, NY Remote (team dependent) Internship details 12-week program: September 21 to December 11, 2026 Paid internship Remote or hybrid work (based on team) Application note Applying to this position enters candidates into consideration for multiple machine learning internship roles across Pinterest’s ML teams. Submit only one application within the USA or Canada; multiple applications may delay review.

Columbia University’s Master's in Applied Analytics program is actively seeking accomplished industry professionals to join as part-time Lecturers for the graduate-level course on Managing Data.The Fundamentals of Data Engineering course equips students with essential knowledge to confidently manage data. As analytic teams collaborate with technology partners, it's crucial to understand team-specific languages and techniques that may hinder cooperation. This course offers a comprehensive overview of data technology concepts, including database engines and related technologies, while introducing foundational data principles, governance processes, and organizational requirements necessary to ensure data quality and address related challenges.Key ResponsibilitiesConduct engaging lectures, instructional activities, and facilitate classroom discussions while attending all class sessions.Provide guidance and support to students by addressing their concerns and inquiries.Assess and grade student assignments and evaluations.Hold regular office hours for student consultations.

The School of Professional Studies at Columbia University is actively seeking experienced industry professionals to join our team as Adjunct Lecturers in the exciting field of Project Management for the upcoming Fall 2026 semester. As part of our commitment to providing top-notch education, you will have the opportunity to develop and teach in-person courses in our innovative M.S. in Project Management program, designed to equip students with essential strategic, analytical, and leadership skills necessary for successful project management across diverse industries.For a detailed overview of the program's curriculum, please click here. Interested candidates are encouraged to specify their areas of expertise in their cover letters, particularly indicating their qualifications to teach one or more of the following core courses:Project Management Fundamentals: Understand the core principles, frameworks, and methods essential for effective project management.Project Planning, Scheduling, and Control: Explore the foundations of project planning, critical path analysis, and performance monitoring.Finance and Accounting for Managers: Apply financial principles within the context of project management.Leadership and Team Dynamics: Learn the principles of leadership, team collaboration, and high-performance team management.Capstone Project: Engage in a real-world, project-based capstone that synthesizes learning across the curriculum.Key Responsibilities:Facilitate dynamic in-person lectures, instructional activities, and engaging classroom discussions.Assess student submissions, providing timely feedback and grades.Serve as the primary point of contact for student inquiries and concerns.Conduct weekly office hours to support student learning.Prepare and maintain course materials in Canvas, Columbia University's learning management system.New part-time lecturers must complete Canvas training upon appointment.Participate in Project Management faculty meetings.If responsible for course design, additional duties include:Developing course objectives that align with broader program learning outcomes.Creating activity maps that connect course activities with objectives to ensure industry relevance.Drafting a comprehensive syllabus (course description, schedule, grading criteria, and assessments) for committee review and approval.Collaborating with Instructional Design to develop course materials through an interactive process.

The School of Professional Studies at Columbia University is actively seeking qualified candidates for the role of Adjunct Associate Faculty in the graduate-level course on Financial Securities Analysis and Portfolio Management. This part-time position offers a unique opportunity for individuals to gain valuable experience in graduate-level instruction at one of the nation's premier educational institutions.This course delves into the intricate world of financial securities, equipping students with the analytical tools necessary to evaluate financial assets and devise effective investment strategies. It serves as a comprehensive introduction to key investment topics that are crucial for those pursuing careers in investment analysis or portfolio management.Key Responsibilities:Participate in all class sessions, assist in instructional duties, lead breakout discussions, and facilitate engaging classroom interactions.Deliver lectures, oversee instructional activities, and actively participate in classroom conversations.Assess and grade student assignments and evaluations as directed by the course Lecturer.Address student inquiries and concerns, providing support and guidance throughout the course.

About Us:At Fireworks AI, we are pioneering the future of generative AI infrastructure. Our platform is recognized for delivering the highest-quality models with the fastest and most scalable inference capabilities in the industry. Proudly benchmarked as a leader in LLM inference speed, we are at the forefront of innovation with projects like function calling and multimodal models. As a Series C company valued at $4 billion, we are supported by prestigious investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. Our team comprises ambitious builders, many of whom hail from Meta PyTorch and Google Vertex AI.The Role:As an Applied Machine Learning Engineer, you will play a crucial role in bridging the gap between advanced AI research and practical applications. Your responsibilities will include developing, fine-tuning, and operationalizing machine learning models that deliver significant business value and enhance user experiences. This hands-on engineering position demands a blend of deep technical expertise and a strong customer-centric approach to create scalable AI solutions.Key Responsibilities:Customer Success: Collaborate with the Go-To-Market (GTM) team, including Account Executives and Solutions Architects, to ensure seamless integration and successful deployment of machine learning solutions.Demo / Proof of Concept (PoC): Develop and present engaging PoCs that showcase the capabilities of our AI technology.Application Build: Design, develop, and deploy end-to-end AI-powered applications customized to meet customer needs.Platform Features / Bug Fixes: Contribute to the internal machine learning platform by adding features and resolving issues.New Model Enablements: Integrate and enable new machine learning models within the existing platform or client environments.Performance Optimizations: Enhance the performance, efficiency, and scalability of deployed models and applications.Partnership Enablement: Collaborate closely with partners to facilitate joint AI solutions and ensure effective collaboration.