Applied AI Engineer

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.

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.

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.

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.

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 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 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.

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.

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.

Join Our Team at RebarRebar is revolutionizing the operating systems used by commercial HVAC, electrical, and plumbing suppliers and subcontractors. In the past year, our initial quoting product has successfully scaled to processing thousands of quotes weekly, and we've doubled our revenue in 2026 while gaining traction among top suppliers across North America. Fresh from securing a $14M Series A investment from leading construction technology investors, we are poised for our next growth phase with AI at the core of our innovations.We are seeking a Principal Deep Learning Engineer who possesses a strong background in modern neural network techniques and proficiency in PyTorch. You will be instrumental in advancing computer vision applications in real-world settings. As part of a tight-knit, highly skilled team, you will focus on delivering practical, production-ready machine learning systems—from building data pipelines to developing finely-tuned models—within a dynamic startup environment.This position is ideal for individuals who thrive on working closely with models, refining training workflows, and tackling novel engineering challenges. Our work transcends mere model inference; we create training workflows, develop robust evaluation pipelines, and construct systems that enhance standard model usage.

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.

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.

Join Thread AI as an Applied AI Strategist and be at the forefront of transforming enterprise operations through innovative AI solutions. At Thread AI, we are dedicated to simplifying the complex landscape of AI-native workflow orchestration for enterprises and public sector agencies.Our team, based in the heart of New York, comprises skilled AI professionals, product specialists, and engineering experts with a proven track record of managing intricate workflows and infrastructure. We invite you to become a part of our dynamic team that is committed to pushing the boundaries of what AI can achieve.Your RoleAs an Applied AI Strategist, you will serve as the vital link between our composable AI infrastructure and the multifaceted realities of our clients' businesses. Collaborating with a dedicated team of Applied Engineers, you will deploy our platform to tackle the most pressing operational challenges faced by enterprises today.Your core mission will be to integrate disparate workflows and raw ambitions into a cohesive understanding of the challenges at hand, identifying how AI agents can offer solutions and where tangible impacts can be realized. By immersing yourself in our clients' complex processes, you will design AI solutions that revolutionize their operational methodologies. This role demands a curious and analytical mindset, a strong intuition for value-driven workflows, and a deep sense of user empathy, empowering our clients to enhance their capabilities.Key ResponsibilitiesDeep-Dive Discovery: Conduct onsite assessments and engage with customer stakeholders to identify significant bottlenecks and high-impact opportunities for AI automation.Solution Architecture: Utilize the Lemma platform to develop tailored agents and workflows, actively configuring logic and integrations to address specific user challenges.Technical Integration: Collaborate closely with our Applied AI Engineering team to facilitate seamless connections for customers between APIs, data sources, and models within the Lemma platform.User Enablement: Lead training sessions to ensure AI solutions align with user needs and generate measurable impacts on their operations.Strategic Reporting: Present deployment outcomes and future roadmap proposals to diverse audiences, from technical leads to C-suite executives.Product Feedback Loop: Work alongside our Software Engineering and Product Design teams to integrate field intelligence into the core Thread AI platform.

Join Thread AI as an Applied AI EngineerAt Thread AI, we are pioneering the development of an AI-native workflow orchestration engine. We seek passionate individuals to be part of our dynamic team, dedicated to simplifying infrastructure for enterprises and public sector agencies eager to harness the full potential of AI.Based in New York, our thriving team comprises specialists in AI, product development, and engineering, all with proven experience in managing intricate workflows and infrastructure.Our Engineering CultureWe pride ourselves on maintaining a tight-knit technical team that integrates engineering, research, design, product, and operational excellence. Our philosophy emphasizes a flat organizational structure and collaborative environment, enabling us to innovate rapidly and create superior products compared to larger, hierarchical organizations.Your RoleAs an Applied AI Engineer, you will be instrumental in architecting and implementing robust AI workflows. Daily, you will design end-to-end customer workflows, oversee their transition to production, and address real-world challenges. Your responsibilities will include crafting innovative, scalable, and high-performance software solutions that align with both customer needs and our strategic goals. You will collaborate closely with our sales and marketing teams to develop forward-thinking prototypes that will guide the future product and infrastructure direction of Thread AI and our clients.

About NevisNevis is at the forefront of revolutionizing wealth management with the world's first AI-driven platform. In less than a year, we have successfully managed over $50 billion in assets, with projections to surpass $100 billion by year-end.With support from leading investors, including Sequoia Capital, ICONIQ, and Ribbit, we've raised $40 million, making us one of the top-funded and fastest-growing Series A startups in Europe.The RoleWe are seeking a passionate and skilled AI Engineer to join our dynamic team at Nevis. You will be instrumental in developing our next-generation AI-focused wealthtech products, tackling key challenges faced by our business clients through innovative LLM-driven automation pipelines.Your work will involve utilizing state-of-the-art LLM models and collaborating with industry-leading vendors to enhance our platform's reasoning capabilities, consistently setting the standard for high-quality model outputs.As part of a small, elite team comprising top engineers and product developers, including the former Head of AI at Revolut, you will have the opportunity to make a significant impact on one of the largest industries globally.Your ResponsibilitiesDesign and create LLM and ML-based features across Nevis’ platform.Collaborate with cross-functional teams to transition new AI capabilities from concept to production.Establish best practices for AI development, testing, observability, and reliability.Continuously monitor and refine the performance and reasoning quality of our AI products.Engage with product and design teams to prototype and enhance new AI features and products.Keep abreast of the latest advancements in the generative AI space, including agentic systems, reasoning capabilities, and context engineering.Your QualificationsHands-on experience with large language models (LLMs).Demonstrated success in solving real-world challenges using AI/ML.Strong statistical and data analysis skills.STEM degree from a reputable university.Enthusiasm for transformative AI technologies.Product-driven mindset, emphasizing practical applications over theoretical concepts.

The OpportunityJoin us at mecka.ai as a Core ML Engineer specializing in Deep Learning Architecture. In this pivotal role, you will spearhead enhancements to our model architecture across all pipelines.This position emphasizes foundational deep learning engineering over applied machine learning. We seek an engineer adept at creating, debugging, and refining internal model architectures from the ground up, moving beyond mere utilization of pre-existing models or standard fine-tuning.Our current ML systems predominantly utilize frame-by-frame models, yet our data is inherently temporal. Your primary responsibility will be transforming and optimizing these models for temporal inference—a crucial factor in unlocking pipeline performance.Additionally, you will become the key resource for model-level debugging, architecture design, and optimization throughout our organization. This is a high-impact, deeply technical role suited for someone who possesses a keen architectural mindset.Key ResponsibilitiesImmediate FocusTemporal Model Conversion: Transition frame-by-frame models to temporal architectures that harness sequential data.Benchmark and validate temporal models against existing frame-based baselines.Ongoing TasksLead enhancements in model architecture across all pipelines (e.g., CV, pose estimation).Tune and debug ML models at the architecture level—modify structural code, craft custom layers, and address the fundamental mathematics rather than relying solely on high-level APIs or hyperparameter tuning.Profile and optimize model performance metrics, including latency, throughput, and memory usage.Assess and integrate new architectures, training strategies, and optimization techniques.Collaborate with CV, ML, and infrastructure teams to deploy enhanced models.