CVPR 2025 Career Opportunities

Location USA, NY, New York City USA, WA, Seattle USA, CA, Palo Alto

Description Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.

The Ad Response Prediction team in the Sponsored Products organization builds GenAI-based shopper understanding and audience targeting systems, along with advanced deep-learning models for Click-through Rate (CTR) and Conversion Rate (CVR) predictions. We develop large-scale machine-learning (ML) pipelines and real-time serving infrastructure to match shoppers' intent with relevant ads across all devices, contexts, and marketplaces. Through precise estimation of shoppers' interactions with ads and their long-term value, we aim to drive optimal ad allocation and pricing, helping to deliver a relevant, engaging, and delightful advertising experience to Amazon shoppers. As our business grows and we undertake increasingly complex initiatives, we are looking for entrepreneurial, and self-driven science leaders to join our team.

The NVIDIA Retriever Team is seeking an Applied Research Intern who will work on the next generation of retrieval pipelines for RAG, with a focus on modalities beyond text. You’ll join a team of experienced Research Scientists, ML and Software Engineers developing NVIDIA’s components for enterprise RAG applications, including but not limited to embedding, ranking, object/text detection, OCR, and llm-as-a judge models or highly optimized containers.

At NVIDIA, we are building the framework upon which production RAG systems are based. We have contributed to top research models in the text embedding space, topping the MTEB leaderboard and have developed commercially viable versions of these models for use in production systems by our customers.

Come be a part of our world-class team building the future of Retrieval!

What you’ll be doing:

• Working with our team of researchers to fine-tune information retrieval models and develop pipelines for text, image, video, audio, and other modalities content.
• Exploring and crafting datasets, designing metrics, running experiments, and evaluating models in order to develop standard methodologies. These methodologies will offer customers clear guidance on which models and pipelines to apply in specific contexts.
• Helping ML Engineers bring new Retrieval models to production as NVIDIA Inference Microservices (NIMs) or blueprints
• Writing blog posts, documentation, training materials and potentially papers, that help customers understand and take advantage of our research
• Keeping up to date with the latest developments in Retrieval across academia and industry

What we need to see:

• Pursuing a PhD in Computer Science or other relevant technical fields
• Excellent Python programming skills and a strong understanding of the Python deep learning ecosystem (in particular PyTorch)
• Excellent knowledge of the current state of Deep Learning, including experience fine-tuning state of the art Large Language Models and Computer Vision models
• Strong communication skills and the ability to share and communicate your ideas clearly through blog posts, papers, kernels, GitHub, etc.

Ways to stand out from the crowd:

• Strong research track record and publication record at top-tier conferences
• Knowledge in multi-GPU and multi-node training
• Prior background and/or academic publication in Retrieval research
• Prior work experience and/or academic publication in (multimodal) Large Language Models

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

The hourly rate for our interns is 30 USD - 90 USD. Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience. You will also be eligible for Intern benefits. NVIDIA accepts applications on an ongoing basis. ​

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Location USA, WA, Seattle USA, NY, New York USA, CA, Palo Alto

Description In Demand Tech, we're revolutionizing digital advertising. Our products deliver on Amazon.com and beyond to TV, Twitch, and third-party websites. We bring advertising to brands of all sizes with rich creative experiences (images, video, text) and brand-first advertising goals.

The Response Prediction team sits at the heart of this mission. We build deep-learning models to predict consumer responses to ads that serve internet-scale traffic. Our goal is to accurately predict shopper responses to ads across a variety of devices, contexts, and marketplaces. By meticulously analyzing shopper interactions and their value, we enable the most effective ad allocation and pricing strategies, crafting advertisements that are not only relevant and engaging but also enrich the shopping experience.

Amidst rapid growth and evolving challenges, Demand Tech seeks a Principal Scientist with a deep passion for data, innovation, and the drive to explore new frontiers. This role is perfect for a leader capable of inspiring our team, pioneering deeply technical strategies, and playing a crucial role in crafting world-class advertising solutions. If you're ready to lead in a culture that prioritizes experimentation, teamwork, and ownership, join us. Together, we'll lead the advancement of brand advertising, pushing boundaries to ensure our continued success and growth.

Location USA, WA, Seattle USA, VA, Arlington USA, NY, New York USA, CA, Palo Alto

Description The Sponsored Products & Brands team is looking for a Sr. Principal Scientist to help our millions of shoppers intuitively navigate our vast inventory by harnessing the power of GenAI and large language models.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, SPB helps merchants, retail vendors, and brand owners succeed via advertising, which grows the incremental sales of their products sold through Amazon. The SPB team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

As a Senior Principal Scientist in Sponsored Products, you will have deep subject matter expertise in the area of large language models and generative AI across various modalities. You will work with multiple teams of scientists and engineers to translate business and functional requirements into concrete deliverables. You will invent new product experiences that enable our shoppers to easily navigate our vast inventory either via search queries, multi-turn conversations, or other modes of input. You will use your expertise to process shopper behavior and product catalog information to generate accurate shopper representations and use it to accurately predict shoppers propensity to engage with our products. You will have the opportunity to invent new approaches that help our advertisers achieve better performance using natural language as the interface. Your inputs will shape how our marketplace understands the shopper and advertiser context to present delightful discovery opportunities to our shoppers.

You will liaise with internal Amazon partners and work on bringing state-of-the-art LLM/GenAI models to production. You will stay abreast of the latest developments in the field of GenAI and identify opportunities to improve the efficiency and productivity of the team. You will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of of applied scientists, and engineers. Finally, you will work with academic partners to support our in-house talent with direct access to cutting edge research and mentoring.

University of Surrey, Guildford, UK

This research post is part of the multimillion GBP EPSRC-funded SustaPack Prosperity Partnership project between the University of Surrey and Pulpex Ltd. As a research fellow, you will help to make the paper bottle a reality through your fundamental research on autonomous quality control.

Plastic packaging persists in the environment and is difficult to recycle. There is a growing demand for alternative materials to use as containers for liquids. Pulpex Ltd. (https://www.pulpex.com) are developing a new type of bottle made from cellulose fibres. The Pulpex bottle uses sustainable materials, can be recycled in existing paper waste-streams, can naturally degrade if not recycled, and has a carbon footprint 30% less than poly(ethylene terephthalate).

Specialist coatings are needed for the bottles to hold liquids and to enable a long shelf-life for the products contained within them. You will work as part of a team of three post-doctoral fellows and a PhD student at the University of Surrey along with engineers from Pulpex.

The project is well funded to allow training opportunities, travel to use national facilities, and conference attendance. There will be opportunities to visit collaborators’ sites and access national facilities. You will be provided with mentorship for personal and professional development to advance your future career. This project will be an excellent entry into the field of sustainable materials which are rapidly growing in use.

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. We are seeking a software engineering intern to join the Omniverse Replicator team to assist in cutting edge research aimed at accelerating how simulations are leveraged to train the next generation of robotics models. Our team's mission is to accelerate the development of autonomous systems and shape the future of robotics and AI.

What you’ll be doing:

• Develop and evaluate novel perception approaches from synthetic simulation on robotics tasks that optimize for learning performance and generalizability.
• Develop benchmarks to validate robot task performance and generalizability to novel scenarios and out-of-distribution events.
• Collaborate with research and engineering teams across NVIDIA such as GR00T and IsaacLab to integrate and validate novel approaches to robot training.

What we need to see:

• Pursuing a BS or MS in Computer Science or related field.
• Experience in software development with Python and the deep-learning software stack (Pytorch, Tensorflow, Jax, etc.).
• Background with reinforcement learning, imitation learning, sensor simulation and synthetic data generation.

Carnegie Mellon University, Pittsburgh

Description

Location RI, Carnegie Mellon University, Pittsburgh, USA

Description

NVIDIA is searching for a Senior Engineer to lead robotics benchmarking efforts across software-in-the-loop (SIL) and hardware-in-the-loop (HIL) systems for Physical AI applications. This is a unique opportunity to shape the future of intelligent machines by developing scalable, accurate, and high-fidelity benchmarking tools that drive innovation in autonomy, robotics, and AI at the edge.

As part of our team, you’ll work closely with world-class engineers, researchers, and product teams to evaluate performance and reliability of robotic systems under real-world and simulated conditions. If you're excited by the challenge of designing advanced benchmarking frameworks and contributing to the evolution of robotics and AI, we’d love to hear from you.

What You’ll Be Doing:

• Design and own the development of robust benchmarking pipelines for SIL and HIL setups across NVIDIA’s robotics stack.
• Define key performance indicators and success metrics for evaluating robotic systems dedicated to perception, planning, and control.
• Develop automated testing frameworks that integrate with simulation environments and physical robots to assess system performance and reliability.
• Engage with versatile teams encompassing hardware, software, systems, and applied research to ensure alignment on evaluation goals and methodologies.
• Identify gaps in current testing infrastructure and propose solutions that improve coverage, scalability, and accuracy. Drive the benchmarking strategy for end-to-end evaluation of real-world robotic use cases, including performance under edge cases and long-tail scenarios.
• Mentor junior engineers and provide technical leadership across projects.

You have solid experience in Computer Graphics with relation to machine learning, e.g., in the areas of neural graphics, rendering, scientific visualization or graphical simulation? You want to deepen your research in a collaborative fashion within a group of closely operating Visual Computing and Sensorics chairs?

In our team we conduct Computer Graphics research in close vicinity to machine learning and computer vision, involving, for instance, range or light-field cameras. We intensively collaborate with Sensorics chairs within the Center for Sensor Systems (ZESS), giving us access to unique sensor and camera expertise and hardware, and with computer vision and machine learning groups that generates a large synergetic research momentum.

We are looking for an enthusiastic and open-minded senior research (an Academic Councilor is similar to a Lecturer/Senior Lecturer) who is eager to conduct Computer Graphics related research and teaching in an interdisciplinary setting and ramp up their own projects. You will be given the opportunity to conduct independent research and teaching in your area of interest, which are ideally related to machine learning, such as neural graphics, rendering, scientific visualization, or graphical simulation. We will support independent activities in the acquisition of third-party funded research projects to foster your own team.

With appropriate performance, the appointment to an adjunct professorship is possible and is supported by the head of the chair. Please apply via https://jobs.uni-siegen.de with job ID 6344, or send an email to andreas.kolb@uni-siegen.de in case you have any question about this open position. Visit our website https://www.cg.informatik.uni-siegen.de/ or the ZESS website https://www.zess.uni-siegen.de to learn more about the working environment.