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Vienna, Austria
Conference
ICLR 2024
May 7 - 11, 2024
Vienna, Austria

Overview

The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.

Sponsorship Details

Gold
Booth #12
Conference website

Accepted publications

Workshops

ICLR 2024 Workshop on AI4DifferentialEquations in Science
May 11
https://ai4diffeqtnsinsci.github.io
Self-supervision improves diffusion models for tabular data imputation
Yixin Liu, Ajanthan Thalaiyasingam, Hisham Husain, Vu Nguyen
2024
Machine learning
Comparing and contrasting deep learning weather prediction backbones on navier-stokes dynamics
Matthias Karlbauer, Danielle Maddix Robinson, Abdul Fatir Ansari, Boran Han, Gaurav Gupta, Yuyang (Bernie) Wang, Andrew Stuart, Michael Mahoney
2024
Machine learning
Neural ode for multi-channel attribution
Yudi Zhang, Oshry Ben-Harush, Siyu Zhu, Dennis Liang, Kent Ken, Daryl Hammett
2024
Machine learning
ICLR 2024 Workshop on Data-centric Machine Learning Research
May 11
https://dmlr.ai/
Bidirectional long-range parser for sequential data understanding
George Leotescu, Daniel Voinea, Alin-Ionut Popa
2024
Machine learning
ICLR 2024 Workshop on Generative Models for Decision Making
May 11
Website: https://sites.google.com/view/genai4dm-iclr2024

Amazon paper: Learning an inventory control policy with general inventory arrival dynamics
ICLR 2024 Workshop on LLM Agents
May 11
https://llmagents.github.io/
Adapting uni-modal language models for dense multi-modal co-reference resolution using parameter augmentation
Sam Osebe, Prashan Wanigasekara, Thomas Gueudre, Thanh Tran
2024
Computer vision
ICLR 2024 Workshop on Practical ML for Low Resource Settings (PML4LRS)
May 11
https://pml4dc.github.io/iclr2024/
Variance-reduced zeroth-order methods for fine-tuning language models
Tanmay Gautam, Youngsuk Park, Hao Zhou, Parameswaran Raman, Wooseok Ha
2024
Machine learning
ICLR 2024 Workshop on Secure and Trustworthy Large Language Models (SET LLM)
May 11
https://set-llm.github.io
Sequence-level certainty reduces hallucination in knowledge-grounded dialogue generation
Yixin Wan, Fanyou Wu, Weijie Xu, Srinivasan Sengamedu, "SHS"
2024
Conversational AI
ICLR 2024 Tiny Papers
May 11
RA-NER: Retrieval augmented NER for knowledge intensive named entity recognition
Zhenwei Dai, Chen Luo, Zhen Li, Xianfeng Tang, Hanqing Lu, Rahul Goutam, Haiyang Zhang
2024
Machine learning
Session-aware product filter ranking in e-commerce search
Hanqing Lu, Xianfeng Tang, Chen Luo, Limeng Cui, Rahul Goutam, Haiyang Zhang, Monica Cheng
2024
Search and information retrieval

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Applied Scientist - Safety ML
US, CA, San Francisco
If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/ About Us: Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role We are looking for applied scientists to solve challenging and open-ended problems in the domain of user and content safety. As an applied scientist on Twitch's Community team, you will use machine learning to develop data products tackling problems such as harassment, spam, and illegal content. You will use a wide toolbox of ML tools to handle multiple types of data, including user behavior, metadata, and user generated content such as text and video. You will collaborate with a team of passionate scientists and engineers to develop these models and put them into production, where they can help Twitch's creators and viewers succeed and build communities. You will report to our Senior Applied Science Manager. This position is located in San Francisco, CA. You Will -Build machine learning products to protect Twitch and its users from abusive behavior such as harassment, spam, and violent or illegal content. -Work backwards from customer problems to develop the right solution for the job, whether a classical ML model or a state-of-the-art one. -Collaborate with Community Health's engineering and product management team to productionize your models into flexible data pipelines and ML-based services. -Continue to learn and experiment with new techniques in ML, software engineering, or safety so that we can better help communities on Twitch grow and stay safe. Perks - Medical, Dental, Vision & Disability Insurance - 401(k) - Maternity & Parental Leave - Flexible PTO - Amazon Employee Discount
Data Scientist - Analytics
US, CA, San Francisco
If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/ About Us: Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role Data is central to Twitch's decision-making process, and data scientists are a critical component to evangelize data-driven decision making in all of our operations. As a data scientist at Twitch, you will be on the ground floor with your team, shaping the way product performance is measured, defining what questions should be asked, and scaling analytics methods and tools to support our growing business, leading the way for high quality, high velocity decisions for your team. As part of the Community Health team at Twitch, you will work directly with product teams to support the safety and well-being of our creators, viewers, and moderators. You will help shape the way we build operational processes, delivering formative insights about the health and safety of our communities, measuring the impact of product improvements and policy changes, and charting a course for future product design and strategy. In a typical week or month, you will contribute to instrumentation, dashboard/report-building, metrics reviews, and ad hoc analysis. You will report to the Data Science Manager for Community Health and Customer Trust and your work will pave the way for high-quality, high-velocity product development that will lead to safer, more rewarding community interactions across the platform. You Will - Become a domain expert in the design of product features to support safer and more rewarding interactions within online communities. - Distill ambiguous product or strategy questions, find clever ways to answer them, and to measure the uncertainty; translate product and strategy questions into metrics, and work with data engineers to dashboard these metrics. - Design and evaluate A/B tests and experiments to measure the effectiveness of front-end product improvements and algorithmic machine learning systems. - Produce ad-hoc reports and insights that help teams move forward with time-sensitive product and strategy decisions. - Maintain a culture of high-quality output and engagement with team members; communicate technical information to technical and non-technical partners; manage ad hoc requests and unexpected obstacles. Perks - Medical, Dental, Vision & Disability Insurance - 401(k) - Maternity & Parental Leave - Flexible PTO - Amazon Employee Discount
Sr. Applied Scientist, AGI Sensory Understanding
IN, KA, Bengaluru
Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers. As a Speech and Language Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in the area of speech and audio understanding technologies including ASR.
Applied Scientist, People eXperience and Technology Central Science Team (PXTCS)
CA, ON, Toronto
Are you motivated to explore research in ambiguous spaces? Are you interested in conducting research that will improve associate, employee and manager experiences at Amazon? Do you want to work on an interdisciplinary team of scientists that collaborate rather than compete? Join us at PXT Central Science! The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. Key job responsibilities As an Applied Scientist for People Experience and Technology (PXT) Central Science, you will be working with our science and engineering teams, specifically on re-imagining Generative AI Applications and Generative AI Infrastructure for HR. Applying Generative AI to HR has unique challenges such as privacy, fairness, and seamlessly integrating Enterprise Knowledge and World Knowledge and knowing which to use when. In addition, the team works on some of Amazon’s most strategic technical investments in the people space and support Amazon’s efforts to be Earth’s Best Employer. In this role you will have a significant impact on 1.5 million Amazonians and the communities Amazon serves and ample scope to demonstrate scientific thought leadership and scientific impact in addition to business impact. You will also play a critical role in the organization's business planning, work closely with senior leaders to develop goals and resource requirements, influence our long-term technical and business strategy, and help hire and develop science and engineering talent. You will also provide support to business partners, helping them use the best scientific methods and science-driven tools to solve current and upcoming challenges and deliver efficiency gains in a changing marke About the team The AI/ML team in PXTCS is working on building Generative AI solutions to reimagine Corp employee and Ops associate experience. Examples of state-of-the-art solutions are Coaching for Amazon employees (available on AZA) and reinventing Employee Recruiting and Employee Listening.
Applied Scientist, Conversational AI ModEling and Learning
CA, ON, Toronto
Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Devices organization where our mission is to build a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Generative AI solutions with LLMs, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including Prompt Engineering and Optimization, Supervised Fine-Tuning, Learning from Human Feedback, Evaluation, Self-Learning, etc. Your work will directly impact our customers in the form of novel products and services.
Applied Scientist, Conversational AI ModEling and Learning
CA, ON, Toronto
Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Devices organization where our mission is to build a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Generative AI solutions with LLMs, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including Prompt Engineering and Optimization, Supervised Fine-Tuning, Learning from Human Feedback, Evaluation, Self-Learning, etc. Your work will directly impact our customers in the form of novel products and services.
Data Scientist, Devices and Services FinTech
US, WA, Seattle
Are you looking for an opportunity to own a large-scale technology problem? Do you enjoy finding patterns and pushing the boundaries of current possibilities? Are you interested in building reliable and scalable systems that support Amazon's growth? If so, Amazon Devices and Services Finance Technology (FinTech) is the perfect place for you! ABOUT THE TEAM Amazon Devices and Services FinTech is the global team that designs and builds the financial planning and analysis tools for a wide variety of Devices` new and established organizations. From Kindle to Ring and even new and exciting companies like Kuiper (our new interstellar satellite play), this team enjoys a wide variety of complex and interesting problem spaces. They are almost like FinTech consultants embedded in Amazon. ABOUT THIS ROLE The Amazon Devices and Services FinTech team is expanding our data science team that is building a forecasting solution for the Amazon Devices and Services Finance organization, and we are looking for a Data Scientist to join us. As a data scientist, you will dive deep into data from across Amazon's finance organization, extract new insights, drive investigations and algorithm development, and interface with technical and non-technical customers. You will leverage your data science expertise and communication skills to pivot between delivering science solutions, translating knowledge of finance and operational processes into forecasting models, and communicating insights and recommendations to audiences of varying levels of technical sophistication in support of specific business questions, root cause analysis, planning, and innovation for the future. Key job responsibilities - Create various forecasts, including but not limited to Operational Expenses, and drive adoption of these forecasts by various teams within Amazon for financial and operations planning - Continuously innovate through research and the application of the latest machine learning techniques to drive forecasting accuracy improvement - Perform exploratory data analysis to identify business opportunities and develop a plan to address them - Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations - Build customer-facing reporting tools to provide insights and metrics which track forecast performance and explain variance - Utilize code (Python, R, Scala, SQL, etc.) for analyzing data and building statistical and machine/deep learning models A day in the life In a typical day as a data scientist at Amazon FinTech, you'll begin by delving into complex datasets, applying your technical expertise in feature engineering and exploratory data analysis to uncover valuable insights. You'll utilize both traditional time series forecasting techniques as well as more advanced machine learning algorithms to build accurate and reliable forecasting models that solve complex business problems like Operational Expense (OpEx) Forecasting. Collaboration with business, engineering, and partner teams is essential, as you'll translate your data-driven forecasts into actionable insights that align with strategic goals. Throughout the day, you'll innovate by adapting new forecasting methods, ensuring your solutions are stable, scalable, and fault-tolerant. Your strong communication skills and attention to detail will help you manage and integrate large datasets, solve unstructured problems, and drive projects to completion in a fast-paced, dynamic environment. Join us and be a part of our dynamic team, driving the future of financial technology at Amazon.
Applied Scientist, Artificial General Intelligence
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
Applied Scientist, Amazon
US, WA, Seattle
The XCM (Cross Channel Cross-Category Marketing) team seeks an Applied Scientist to revolutionize our marketing strategies. XCM's mission is to build the most measurably effective, creatively impactful, and cross-channel campaigning capabilities possible, with the aim of growing "big-bet" programs, strengthening positive brand perceptions, and increasing long-term free cash flow. As a science team, we're tackling complex challenges in marketing incrementality measurement, optimization and audience segmentation. In this role, you'll collaborate with a diverse team of scientists and economists to build and enhance causal measurement, optimization and prediction models for Amazon's global multi-billion dollar fixed marketing budget. You'll also work closely with various teams to develop scientific roadmaps, drive innovation, and influence key resource allocation decisions. Key job responsibilities 1) Innovating scalable marketing methodologies using causal inference and machine learning. 2) Developing interpretable models that provide actionable business insights. 3) Collaborating with engineers to automate and scale scientific solutions. 4) Engaging with stakeholders to ensure effective adoption of scientific products. 5) Presenting findings to the Amazon Science community to promote excellence and knowledge-sharing.
Applied Scientist I, BRP (Buyer Risk Prevention)
US, CA, San Diego
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches
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